Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

ANTHROPIC JUST KILLED A DOZEN AI MEMORY STARTUPS WITH ONE BUILT IN TOOL people raised millions to give AI long term memory. Anthropic just shipped it straight into the API. free, no framework, no vector database. it is a folder of files Claude reads and writes. that is it....

N01ennn's profile picture

NO1ennn

4,189 subscribers

42,946 Aufrufe • vor 16 Tagen •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Clude is now available as a custom connector on Anthropic Claude. Giving it persistent memory across every conversation. It remembers your projects, your preferences, and the decisions you make, so you never start from zero again. Use Clude across Chat / Co-Work and Claude Code. Add it in 30 seconds, no API key: 1. In Claude: Customize, Add custom connector URL: Enter your email. That's it. Recap for people unfamiliar: Clude deviates from the traditional vector database that many others bolt onto Claude. We are a cognitive memory system modeled on how human memory works. Think traditional memory systems: Calculator > It computes. Fullstop. Excel > Dynamic, formula run, able to share and manipulate Clude scored 86% on LongMemEval, one of the toughest long-term memory benchmarks. This means less hallucinations to traditional platforms. It scores memories by relevance, recency, and importance, links them into a knowledge graph, and consolidates them over time. Tell Claude something, open a new chat, and watch it remember.
0:39

Clude is now available as a custom connector on Anthropic Claude. Giving it persistent memory across every conversation. It remembers your projects, your preferences, and the decisions you make, so you never start from zero again. Use Clude across Chat / Co-Work and Claude Code. Add it in 30 seconds, no API key: 1. In Claude: Customize, Add custom connector URL: Enter your email. That's it. Recap for people unfamiliar: Clude deviates from the traditional vector database that many others bolt onto Claude. We are a cognitive memory system modeled on how human memory works. Think traditional memory systems: Calculator > It computes. Fullstop. Excel > Dynamic, formula run, able to share and manipulate Clude scored 86% on LongMemEval, one of the toughest long-term memory benchmarks. This means less hallucinations to traditional platforms. It scores memories by relevance, recency, and importance, links them into a knowledge graph, and consolidates them over time. Tell Claude something, open a new chat, and watch it remember.

seb

20,598 Aufrufe • vor 2 Monaten

ANTHROPIC KILLED THE VECTOR DATABASE AND REPLACED IT WITH A FOLDER no embeddings. no black-box retrieval. no special memory tools. the agent just reads and writes a folder the insight: your agent already knows how to use a filesystem. so Anthropic made long-term memory a directory of small markdown files, mounted straight into the agent's sandbox at /mnt/memory the agent manages it with the tools it already has, bash, read, write, edit, grep, and Anthropic auto-injects a note into the system prompt so the agent always knows the memory is there and where to look the result: > every change is an immutable version: full audit trail, point-in-time recovery, redaction > read-only or read-write per store, so many agents can safely share one memory > workspace-scoped and persistent, memory that survives every session end most teams bolt on a vector DB and pray retrieval works. Anthropic went the opposite way: compiled knowledge as plain, human-readable files you can open, diff, and edit yourself and there's a second layer. Anthropic's "Dreaming" runs offline, reviews past sessions and the store, and rewrites it into a cleaner, higher-signal version. the agent literally consolidates memory in its sleep. bookmark this. the most production-grade agent memory right now is just a well-organized folder, and Anthropic proved it.
0:50

ANTHROPIC KILLED THE VECTOR DATABASE AND REPLACED IT WITH A FOLDER no embeddings. no black-box retrieval. no special memory tools. the agent just reads and writes a folder the insight: your agent already knows how to use a filesystem. so Anthropic made long-term memory a directory of small markdown files, mounted straight into the agent's sandbox at /mnt/memory the agent manages it with the tools it already has, bash, read, write, edit, grep, and Anthropic auto-injects a note into the system prompt so the agent always knows the memory is there and where to look the result: > every change is an immutable version: full audit trail, point-in-time recovery, redaction > read-only or read-write per store, so many agents can safely share one memory > workspace-scoped and persistent, memory that survives every session end most teams bolt on a vector DB and pray retrieval works. Anthropic went the opposite way: compiled knowledge as plain, human-readable files you can open, diff, and edit yourself and there's a second layer. Anthropic's "Dreaming" runs offline, reviews past sessions and the store, and rewrites it into a cleaner, higher-signal version. the agent literally consolidates memory in its sleep. bookmark this. the most production-grade agent memory right now is just a well-organized folder, and Anthropic proved it.

NO1ennn

13,359 Aufrufe • vor 22 Tagen

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 Aufrufe • vor 29 Tagen

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.
0:34

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

110,658 Aufrufe • vor 2 Monaten

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
0:24

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

58,186 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 2 Monaten

A GUY MAKING $100K/MONTH WITH AI JUST SHOWED HIS ENTIRE SETUP. IT'S ONE FOLDER OF NOTES AND NOTHING ELSE no framework. no $500 course. he opens his screen and it's just obsidian - a plain notes app - wired into claude here's what he did: -> he pulled claude's memory files out of their default folder and dumped them into one vault -> had claude rename and merge them: 107 messy files collapsed into 17 clean ones -> every folder gets one master note that links to all the others that last part is the whole trick the agent reads the master note, follows the links and by the time it's done it has read every file in the folder. one instruction, full context here's the part most people miss: everyone's trying to make the AI smarter. he made the AI's memory smaller fewer files, better organized, all linked. the agent isn't scanning hundreds of notes anymore - it walks a path you built that's why his agent actually finishes jobs instead of forgetting what it was doing halfway through then he goes one step further: at the end of every session, the agent writes its own daily note. what it did, when, indexed at the top so it can find it again in seconds so he never re-explains anything. the agent looks up what it already did now he types "create a campaign for this offer" and walks away. it reads the product notes, reads the process notes, and comes back with the campaign done you don't need any of the complicated agent tools people are selling you. you need structure and instructions save this. the people winning with AI aren't using better models. they're just the only ones who bothered to organize what it remembers
9:56

A GUY MAKING $100K/MONTH WITH AI JUST SHOWED HIS ENTIRE SETUP. IT'S ONE FOLDER OF NOTES AND NOTHING ELSE no framework. no $500 course. he opens his screen and it's just obsidian - a plain notes app - wired into claude here's what he did: -> he pulled claude's memory files out of their default folder and dumped them into one vault -> had claude rename and merge them: 107 messy files collapsed into 17 clean ones -> every folder gets one master note that links to all the others that last part is the whole trick the agent reads the master note, follows the links and by the time it's done it has read every file in the folder. one instruction, full context here's the part most people miss: everyone's trying to make the AI smarter. he made the AI's memory smaller fewer files, better organized, all linked. the agent isn't scanning hundreds of notes anymore - it walks a path you built that's why his agent actually finishes jobs instead of forgetting what it was doing halfway through then he goes one step further: at the end of every session, the agent writes its own daily note. what it did, when, indexed at the top so it can find it again in seconds so he never re-explains anything. the agent looks up what it already did now he types "create a campaign for this offer" and walks away. it reads the product notes, reads the process notes, and comes back with the campaign done you don't need any of the complicated agent tools people are selling you. you need structure and instructions save this. the people winning with AI aren't using better models. they're just the only ones who bothered to organize what it remembers

Paone

23,833 Aufrufe • vor 1 Monat

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 Aufrufe • vor 2 Monaten

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.
0:23

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.

NO1ennn

68,276 Aufrufe • vor 12 Tagen

AN ANTHROPIC ENGINEER LEAKED THIS OBSIDIAN CONVENTION you start with 12 notes and one convention. 6 months later you have 2379 and every one is linked to every one it belongs next to. you never touched the graph. claude did the convention is a domain prefix at the top of every markdown file. six characters. claude reads it, knows where the note belongs, and connects it to the older ones without you ever asking you drop in a new pdf at midnight. claude reads it, writes 8 linked notes, contradicts your old note from march, dates both versions, and pins the one you actually need on top by morning your vault stops being a folder. it becomes a night sky article in the first reply i test things like this on myself and share the results. follow kai if you want to see what's next
0:21

AN ANTHROPIC ENGINEER LEAKED THIS OBSIDIAN CONVENTION you start with 12 notes and one convention. 6 months later you have 2379 and every one is linked to every one it belongs next to. you never touched the graph. claude did the convention is a domain prefix at the top of every markdown file. six characters. claude reads it, knows where the note belongs, and connects it to the older ones without you ever asking you drop in a new pdf at midnight. claude reads it, writes 8 linked notes, contradicts your old note from march, dates both versions, and pins the one you actually need on top by morning your vault stops being a folder. it becomes a night sky article in the first reply i test things like this on myself and share the results. follow kai if you want to see what's next

kai

11,994 Aufrufe • vor 24 Tagen

THE GUY RUNNING CLAUDE CODE AT ANTHROPIC JUST SAID HE DOESN’T PROMPT AI ANYMORE. He writes loops. That’s a huge difference. A prompt tells Claude what to do once. A loop gives Claude a goal. Then Claude keeps checking its own work… Finding mistakes. Writing its next prompt. Trying again. Over and over… Until it actually reaches the target you defined. But here’s what most people miss. A loop is only as smart as the context you give it. That’s exactly why Claude Repositories matter. I broke down how to connect your entire codebase so Claude can actually reason across your project instead of a single file. Full guide below
1:36

THE GUY RUNNING CLAUDE CODE AT ANTHROPIC JUST SAID HE DOESN’T PROMPT AI ANYMORE. He writes loops. That’s a huge difference. A prompt tells Claude what to do once. A loop gives Claude a goal. Then Claude keeps checking its own work… Finding mistakes. Writing its next prompt. Trying again. Over and over… Until it actually reaches the target you defined. But here’s what most people miss. A loop is only as smart as the context you give it. That’s exactly why Claude Repositories matter. I broke down how to connect your entire codebase so Claude can actually reason across your project instead of a single file. Full guide below

kiosa

16,808 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 2 Monaten

THIS GUY TURNED ONE OBSIDIAN VAULT INTO A SHARED BRAIN FOR 5 CLAUDE AGENTS BUILT TO HANDLE 80% OF A SOLO DEVELOPER’S WORK. 00:03 he zooms out and hundreds of connected notes appear on screen. it is the perfect visual for Claude working from one shared project memory instead of starting from zero every session. most developers give Claude 1 file and 1 prompt. this setup gives it the architecture, coding rules, tests, client briefs, and previous decisions before it writes anything. obsidian becomes the memory layer, storing everything in markdown files Claude can read alongside the codebase. every agent works from the same context instead of repeating the same questions. then 5 specialists split the job. one researches, one plans, one codes, one reviews, and one deploys while the developer only controls the important decisions. one vault, 5 agents, 2 model tiers, and a $50 to $150 monthly stack can turn Claude from a chatbot into a small development team.
0:30

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

Gipp 🦅

10,799 Aufrufe • vor 1 Monat

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 Aufrufe • vor 27 Tagen

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.
1:03

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.

Avid

16,279 Aufrufe • vor 3 Monaten

This guy literally told Claude to run every day at 4am. Now it opens his website, writes a blog post, and optimizes it for SEO. Every single day. Zero involvement. Here's how Claude computer use actually works: It looks at your screen. Moves your mouse. Clicks buttons. Opens apps. Completes the full task on its own. No code. No workflow builder. No setup. You just tell it what you want done. And the 4am SEO trick? You schedule it once inside Claude Co-work. Claude runs it every night while you sleep. Your site gets fresh content. You wake up and check the results. That's not a chatbot. That's an AI employee.
11:12

This guy literally told Claude to run every day at 4am. Now it opens his website, writes a blog post, and optimizes it for SEO. Every single day. Zero involvement. Here's how Claude computer use actually works: It looks at your screen. Moves your mouse. Clicks buttons. Opens apps. Completes the full task on its own. No code. No workflow builder. No setup. You just tell it what you want done. And the 4am SEO trick? You schedule it once inside Claude Co-work. Claude runs it every night while you sleep. Your site gets fresh content. You wake up and check the results. That's not a chatbot. That's an AI employee.

Julian Goldie SEO

133,361 Aufrufe • vor 5 Monaten

SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one
1:43

SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one

kai

174,650 Aufrufe • vor 1 Monat

CLAUDE CODE JUST SHIPPED THE FEATURE THAT SOLVES THE BIGGEST PROBLEM EVERY BUILDER HAS WITH AI AGENTS. The problem: Claude starts a task, gets distracted by a sub-problem, goes down a rabbit hole, and never finishes the original thing you asked for. The solution: /goal One command. You set the goal at the start of the session. Claude now has a north star it checks against every action it takes. Not just at the beginning. Throughout the entire session. Every time Claude is about to do something it asks: does this action move me toward the goal the user set or am I drifting? If it is drifting it corrects. If it completes a sub-task it returns to the primary goal. If it hits a blocker it reports back instead of spending 45 minutes solving the wrong problem. This sounds like a small feature. It is not. The reason most people do not trust Claude Code for long autonomous runs is not capability. It is reliability. A Claude Code session that reliably finishes what it started is worth 10 times more than one that is more capable but wanders. /goal is the feature that makes long autonomous sessions reliable. Set the goal. Let it run. Come back to a finished result. Not a result that got 70% done before Claude decided the sub-problem was more interesting. Done. The builders running overnight agent sessions are going to use this command on everything from today forward. Bookmark this. Follow CyrilXBT for every Claude Code feature the moment it ships.
0:24

CLAUDE CODE JUST SHIPPED THE FEATURE THAT SOLVES THE BIGGEST PROBLEM EVERY BUILDER HAS WITH AI AGENTS. The problem: Claude starts a task, gets distracted by a sub-problem, goes down a rabbit hole, and never finishes the original thing you asked for. The solution: /goal One command. You set the goal at the start of the session. Claude now has a north star it checks against every action it takes. Not just at the beginning. Throughout the entire session. Every time Claude is about to do something it asks: does this action move me toward the goal the user set or am I drifting? If it is drifting it corrects. If it completes a sub-task it returns to the primary goal. If it hits a blocker it reports back instead of spending 45 minutes solving the wrong problem. This sounds like a small feature. It is not. The reason most people do not trust Claude Code for long autonomous runs is not capability. It is reliability. A Claude Code session that reliably finishes what it started is worth 10 times more than one that is more capable but wanders. /goal is the feature that makes long autonomous sessions reliable. Set the goal. Let it run. Come back to a finished result. Not a result that got 70% done before Claude decided the sub-problem was more interesting. Done. The builders running overnight agent sessions are going to use this command on everything from today forward. Bookmark this. Follow CyrilXBT for every Claude Code feature the moment it ships.

CyrilXBT

19,586 Aufrufe • vor 3 Monaten

> downloaded Claude Code > thought it was just another AI chatbot > opened it up > found a chat bar > typed a prompt > nothing happened to my files > realized the difference > browser AI waits for you to bring your files > Claude Code goes into your folder > all 45 PDFs > all the transcripts > all the messy Excel sheets > reads them all > remembers them session after session > you never re-explain your project again > so before your next literature review, do this: > create a folder with all your papers > open it in Claude Code > write a CLAUDEmd with your role, field, and writing style > ask it to screen every PDF using your inclusion/exclusion criteria > let it rename, extract, and summarize while you think > the AI didn't replace your scholarship > it eliminated the 6 hours of grunt work before it starts
3:03:53

> downloaded Claude Code > thought it was just another AI chatbot > opened it up > found a chat bar > typed a prompt > nothing happened to my files > realized the difference > browser AI waits for you to bring your files > Claude Code goes into your folder > all 45 PDFs > all the transcripts > all the messy Excel sheets > reads them all > remembers them session after session > you never re-explain your project again > so before your next literature review, do this: > create a folder with all your papers > open it in Claude Code > write a CLAUDEmd with your role, field, and writing style > ask it to screen every PDF using your inclusion/exclusion criteria > let it rename, extract, and summarize while you think > the AI didn't replace your scholarship > it eliminated the 6 hours of grunt work before it starts

Blum

17,260 Aufrufe • vor 3 Monaten

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.
1:54

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

Milind S

12,409 Aufrufe • vor 2 Monaten