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grok bot + obsidian is basically superhuman mode... my agent team now has a second brain... a karpathy-style llm wiki for every bot, every decision, and every piece of research. p.s. this video was made and edited by grok bot in cap (here’s how i set it up in... roughly 5 minutes) 1/ create one obsidian vault on the chief of staff’s computer. make Home.md the door. 2/ create Hunt folders for twitter, github, hacker-news, reddit, product-hunt, and inbox. 3/ create Ship folders for drafts, digests, angles, and builds. 4/ create the CoS wiki: Index, How-it-works, Today, and Decisions. 5/ create Maps for Jarvis, Hooks, and TELOS. 6/ use graph colors: gold for wiki, teal for maps, blue for twitter, green for github. 7/ file first. every note gets a date and a folder. 8/ scouts write into Hunt and never ping you. chat only receives a short digest. 9/ nothing in the vault posts, pays, or sends. the final yes stays human. 10/ run the daily loop: 08:00 IST for the Daily note, then agency reports at 08:14, 14:14, and 20:14. 11/ performance writes to twitter/live-score. staff engineer writes to builds/. 12/ lock decisions in Wiki/Decisions so dead posts don’t get remade. 13/ earn hooks in Maps/Hooks: trend -> foil -> hook family -> artifact -> lock. don't waste time reading this. give it to your agentshow more

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

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

YanXbt

34,987 просмотров • 1 месяц назад

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE FABLE 5 + OBSIDIAN Andrej Karpathy (openai co-founder) shared an architecture that turns Claude into a persistent second brain instead of a basic chat window how it works: > you point Claude Code at an Obsidian vault folder > you drop articles, PDFs, or video transcripts into raw folders > Claude reads the files, updates topic summaries, and cross-references everything > the knowledge base compounds like interest instead of resetting on every new chat the setup is simple: > install and create a local vault directory > open the directory in Claude Code and paste Karpathy's wiki prompt: > > let the agent generate raw, wiki, and CLAUDE.md schema directories > drop any text file into raw and tell the model to ingest it > ask questions across the whole vault and query compiled summaries this eliminates rag database overhead and keeps your local vault organized how do you manage your local knowledge base?

Mr. Buzzoni

89,170 просмотров • 1 месяц назад

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE OPUS 5 + OBSIDIAN Andrej Karpathy (OpenAI co-founder) shared an architecture that turns Claude into a persistent second brain not just a basic chat window how it works: > point Claude Code at an Obsidian vault folder > drop articles, PDFs, or video transcripts into raw > Claude reads them, updates summaries, cross-references everything > the knowledge base compounds like interest, never resets on a new chat the setup: > install create a local vault folder > open it in Claude Code, paste Karpathy's wiki prompt > > let the agent build raw, wiki, and CLAUDE.md folders > drop any file into raw, tell it to ingest > ask questions, get compiled summaries back this skips rag overhead entirely. your vault stays organized on its own run ingest on a schedule and it's loop engineering: sense a new file, plan, write, verify, repeat how do you manage your local knowledge base?

BUILD KARPATHY'S SECOND BRAIN WITH CLAUDE OPUS 5 + OBSIDIAN Andrej Karpathy (OpenAI co-founder) shared an architecture that turns Claude into a persistent second brain not just a basic chat window how it works: > point Claude Code at an Obsidian vault folder > drop articles, PDFs, or video transcripts into raw > Claude reads them, updates summaries, cross-references everything > the knowledge base compounds like interest, never resets on a new chat the setup: > install create a local vault folder > open it in Claude Code, paste Karpathy's wiki prompt > > let the agent build raw, wiki, and CLAUDE.md folders > drop any file into raw, tell it to ingest > ask questions, get compiled summaries back this skips rag overhead entirely. your vault stays organized on its own run ingest on a schedule and it's loop engineering: sense a new file, plan, write, verify, repeat how do you manage your local knowledge base?

Mr. Buzzoni

14,716 просмотров • 4 дней назад

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

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

Ridark

6,959,684 просмотров • 2 месяцев назад

I still don't understand why everyone is not using this yet. Thanks to it, a year ago I increased my income to 17,000 dollars a month Andrey Karpathy, co-founder of OpenAI, published a simple idea that got 16 million views: stop using AI to write code, use it to build a second brain You point Claude Code to a folder, drop any source in there (an article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. It compounds like interest: the more you feed it, the smarter it gets Here is the gist: Install Obsidian, create a vault, open it in Claude Code Paste the file with Karpathy's wiki idea and tell Claude to build it Claude creates three folders: raw for sources, wiki for its pages, CLAUDE which runs everything Drop any source into raw and say "ingest this" Ask questions across everything, forever Five minutes to set up, and you never start with an empty chat again The full step-by-step guide is in the article. Save to bookmarks

I still don't understand why everyone is not using this yet. Thanks to it, a year ago I increased my income to 17,000 dollars a month Andrey Karpathy, co-founder of OpenAI, published a simple idea that got 16 million views: stop using AI to write code, use it to build a second brain You point Claude Code to a folder, drop any source in there (an article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. It compounds like interest: the more you feed it, the smarter it gets Here is the gist: Install Obsidian, create a vault, open it in Claude Code Paste the file with Karpathy's wiki idea and tell Claude to build it Claude creates three folders: raw for sources, wiki for its pages, CLAUDE which runs everything Drop any source into raw and say "ingest this" Ask questions across everything, forever Five minutes to set up, and you never start with an empty chat again The full step-by-step guide is in the article. Save to bookmarks

Bober_smart

2,373,405 просмотров • 1 день назад

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

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

elvis

47,989 просмотров • 4 месяцев назад

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

Mike Futia

17,007 просмотров • 4 месяцев назад

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.

Karpathy method + Claude Code reading your whole Obsidian vault is the smartest second brain on earth. The method is simple and brutal. If you can’t build a thing from scratch, you don’t know it. Tutorials are fake learning and your brain deletes them in 3 days. Most people ignore this. They build a second brain that just sits there, folders of notes nobody reopens, dead text. Point Claude Code at the vault and it wakes up. 5,000 notes, one mind. It reads all of it and answers in your own words and your own proofs, not a model’s guess. Then the loop closes. Want to understand neural nets? Skip the 3-hour video and ask Claude Code to build a tiny one. 200 lines from scratch. Watch it train, break a layer, watch it fail, fix it. It clicks in 20 minutes instead of 3 weeks. The second it lands the note gets written. One idea per file, linked to 10 others, dropped into the vault while the memory is still hot. Now it compounds. Month 1: is 60 notes. Month 6 is 900. Every new note pulls in old ones, so you ask anything and the answer comes from your brain, not the internet. Before: 40 tabs, 6 half read PDF, 0 retained. After: build it once, own it for life. Setup takes 4 minutes. Plain text, no lock-in. A second brain nobody reads is a graveyard. Yours just started thinking.

West Lord

592,073 просмотров • 1 месяц назад

PLUGGED CLAUDE CODE INTO OBSIDIAN AND MY DEAD VAULT STARTED FIRING LIKE A NEURAL NETWORK 13,000 notes written by hand over 4 years, and search worked fine that was the problem, because search only gives back what you already remember well enough to ask for The graph view never helped either, just a pretty picture nobody actually reads Here is what almost nobody uses: Obsidian keeps your entire vault as plain markdown in a folder on disk, with no database, no export, no API to beg for access So an agent doesn't need permission, it needs a path I gave Claude Code the vault directory and one rule don't answer me, read the links It stopped treating notes as files and started treating them as a net, where backlinks became edges and tags became weights and every note it opened dragged 20 more into context Then it wrote a file I never asked for One note welding two clusters 4 years apart an old client teardown and a half-dead idea buried in a daily note from last winter, a connection I had circled for months and never closed The agent closed it on the first pass, not because it was smarter, but because it had no memory of writing either one That's the part nobody says out loud: a second brain is not a memory problem, it's a distance problem, and you are standing too close to your own notes Everyone builds a second brain, nobody gives it a nervous system

PLUGGED CLAUDE CODE INTO OBSIDIAN AND MY DEAD VAULT STARTED FIRING LIKE A NEURAL NETWORK 13,000 notes written by hand over 4 years, and search worked fine that was the problem, because search only gives back what you already remember well enough to ask for The graph view never helped either, just a pretty picture nobody actually reads Here is what almost nobody uses: Obsidian keeps your entire vault as plain markdown in a folder on disk, with no database, no export, no API to beg for access So an agent doesn't need permission, it needs a path I gave Claude Code the vault directory and one rule don't answer me, read the links It stopped treating notes as files and started treating them as a net, where backlinks became edges and tags became weights and every note it opened dragged 20 more into context Then it wrote a file I never asked for One note welding two clusters 4 years apart an old client teardown and a half-dead idea buried in a daily note from last winter, a connection I had circled for months and never closed The agent closed it on the first pass, not because it was smarter, but because it had no memory of writing either one That's the part nobody says out loud: a second brain is not a memory problem, it's a distance problem, and you are standing too close to your own notes Everyone builds a second brain, nobody gives it a nervous system

Spike 1%

12,443 просмотров • 4 дней назад

20 days ago, I connected Claude Code to my newly created instagram handle.. I gained 4.3M views and 6500+ followers in less than a month [ i post Ai generated animated stories ] Full workflow: i let claude study my account before i write another reel.. This is the cleanest content workflow i've built on claude. give it your IG first. 4 prompts handle the rest.. niche research, the reel script, the hook, and the daily automation.. the whole loop is basically, give claude your IG → find what's working → write retention-optimized scripts → engineer the hook → automate the daily output.. ▫️ Setup: give claude your instagram open claude code. claude code has a built-in web tool that browses any public URL. or install any agentic browser like Browser Harness or Firecrawl or Comet browser paste this with your handle filled in: "Browse and pull the last 30 reels and posts. Analyze my recurring topics, top-performing hooks, formats, and engagement patterns. Then map out my actual audience and what they consistently respond to." claude reads your profile, pulls every reel down, and now has the context to personalize every prompt below to YOUR account, not a generic niche. if you're on claude desktop, the same works with firecrawl MCP connected. ▫️ Prompt 1 find what actually goes viral in your niche: "Analyze the highest-performing Instagram Reels, TikToks, and Reddit posts in the [niche] niche from the last 30 days. Identify repeating hooks, visual styles, emotional triggers, and content formats that consistently generate high engagement. Then summarize the 5 strongest content angles optimized for AI-generated content and short-form videos." run this after the setup. you get 5 angles backed by what's already working in your niche, cross-checked against what's already working on YOUR account. ▫️ Prompt 2 write a high-retention reel script "Write a short-form Instagram Reel script about [topic] with an aggressive hook in the first 2 seconds. Create immediate curiosity, tension, or controversy to stop scrolling, then deliver a fast and satisfying payoff. Keep it under 30 seconds and optimize the structure for watch time, replays, comments, and shares. Finish with a subtle CTA." the line that matters: "optimize the structure for watch time, replays, comments, and shares." claude writes for the metrics, not just the word count. ▫️ Prompt 3 engineer better hooks "Study the top-performing Reels in [niche] and break down the hook structure, pacing, and emotional triggers used in the first 3 seconds. Then generate 5 new hook variations that are even more curiosity-driven, emotionally charged, and optimized to stop scrolling instantly. Focus on triggers like surprise, fear, ego, urgency, or desire." most reels die in the first 2 seconds. this prompt has claude reverse-engineer what already works, then give you 5 sharper versions to swap in. ▫️ Prompt 4 automate the whole workflow "Build a complete AI-powered content workflow for Instagram in the [niche] niche. The system should identify trending topics daily, generate high-retention scripts, create matching AI visuals, turn them into short-form videos, and generate optimized captions and hashtags. Structure everything as a repeatable workflow designed for consistent daily posting and growth." once the niche and script structure are validated, this turns it into a daily loop. one prompt that handles topic → script → visual → video → caption. these 4 prompts are the building blocks. the setup is what makes them yours. your real value is in the [niche] you plug in. content workflow built in one weekend, daily posting on autopilot from monday.

Axel Bitblaze 🪓

199,569 просмотров • 2 месяцев назад

A 95-minute action movie normally costs $50,000,000+ but Higgsfield just made one for under $500K in 14 days. And today they open-sourced every prompt behind it. You’re COOKED if you scroll past this: 1. Hell Grind: a full 95-minute AI feature film 2. Traditional budget for this genre: ~$50M 3. Their cost: under $500K. 100x cheaper. 4. Timeline: 14 days. Not 14 months. 5. $400K of that was pure compute 6. 16,181 generations for the first 25 minutes alone 7. 253 final shots. A 64:1 curation ratio. 8. That’s $500K of trial-and-error, distilled 9. And every winning prompt is now public 10. Every asset. Every scene. $0. 11. Studios would pay 6 figures for this exact knowledge 12. Open the kit, pick any scene 13. Reverse engineer how they kept one character’s face consistent for 95 minutes 14. That’s the hardest problem in AI video — solved in public 15. Remix a scene, post your breakdown 16. First movers on new techniques always eat 17. This is the opening move for the $1M Higgsfield Global Film Festival 18. The playbook for winning it is sitting in a free folder There’s a $1M festival on the line and the winning playbook is free. If you’re serious about getting paid for AI video in 2026, this is the best risk-free shot you’ll get. Open the kit tonight, pick ONE scene, and rebuild it. That’s your film school for 2026 and it costs you nothing. (clip attached — straight from the film)

A 95-minute action movie normally costs $50,000,000+ but Higgsfield just made one for under $500K in 14 days. And today they open-sourced every prompt behind it. You’re COOKED if you scroll past this: 1. Hell Grind: a full 95-minute AI feature film 2. Traditional budget for this genre: ~$50M 3. Their cost: under $500K. 100x cheaper. 4. Timeline: 14 days. Not 14 months. 5. $400K of that was pure compute 6. 16,181 generations for the first 25 minutes alone 7. 253 final shots. A 64:1 curation ratio. 8. That’s $500K of trial-and-error, distilled 9. And every winning prompt is now public 10. Every asset. Every scene. $0. 11. Studios would pay 6 figures for this exact knowledge 12. Open the kit, pick any scene 13. Reverse engineer how they kept one character’s face consistent for 95 minutes 14. That’s the hardest problem in AI video — solved in public 15. Remix a scene, post your breakdown 16. First movers on new techniques always eat 17. This is the opening move for the $1M Higgsfield Global Film Festival 18. The playbook for winning it is sitting in a free folder There’s a $1M festival on the line and the winning playbook is free. If you’re serious about getting paid for AI video in 2026, this is the best risk-free shot you’ll get. Open the kit tonight, pick ONE scene, and rebuild it. That’s your film school for 2026 and it costs you nothing. (clip attached — straight from the film)

ALEX SUZUKI

592,614 просмотров • 17 дней назад

I found 7 free Polymarket trading bots on GitHub for 7 different trading situations… Each of these bots comes with a detailed step by step setup and usage guide in English: 1. This bot includes 118+ ready to use strategies and tools for trading on prediction markets (Momentum, Binance-Polymarket latency, Penny Clipper, Smart Routing, Expiry Fade, DCA bots and more). Built by a Cambridge computer science student who won a hackathon with this trading bot. GitHub: 2. This bot automatically manages all your Polymarket limit orders to maximize liquidity rewards. GitHub: 3. A weather bot from a Chinese dev, that analyzes multiple sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the most accurate temperature data and generate a detailed weather report for a specific city and day. GitHub: 4. A bot that automatically searches for arbitrage opportunities between Polymarket and Kalshi. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, whale alerts, spread farming, sports trading and more… GitHub: 6. A smart money trading bot - it looks for the most successful traders in selected markets, filters them by Pnl + win rate, and then creates a list for automated copy trading. GitHub: 7. A large collection of 20+ free trading bots for prediction markets. GitHub: Every bot here has a Dry Run mode, so you can test it on real markets without risking any funds.

I found 7 free Polymarket trading bots on GitHub for 7 different trading situations… Each of these bots comes with a detailed step by step setup and usage guide in English: 1. This bot includes 118+ ready to use strategies and tools for trading on prediction markets (Momentum, Binance-Polymarket latency, Penny Clipper, Smart Routing, Expiry Fade, DCA bots and more). Built by a Cambridge computer science student who won a hackathon with this trading bot. GitHub: 2. This bot automatically manages all your Polymarket limit orders to maximize liquidity rewards. GitHub: 3. A weather bot from a Chinese dev, that analyzes multiple sources in real time, like forecasts, airport data and aviation observations (METAR + SPECI) to get the most accurate temperature data and generate a detailed weather report for a specific city and day. GitHub: 4. A bot that automatically searches for arbitrage opportunities between Polymarket and Kalshi. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, whale alerts, spread farming, sports trading and more… GitHub: 6. A smart money trading bot - it looks for the most successful traders in selected markets, filters them by Pnl + win rate, and then creates a list for automated copy trading. GitHub: 7. A large collection of 20+ free trading bots for prediction markets. GitHub: Every bot here has a Dry Run mode, so you can test it on real markets without risking any funds.

Recogard

42,002 просмотров • 2 месяцев назад

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

Machina

59,261 просмотров • 6 дней назад

This Chinese guy built a Second Brain in Obsidian and every morning gets 3 trading ideas that brought him $180,000 in 6 months. Inside he runs a pipeline of 6 workflows on N8N that automatically pulls every read article, listened podcast, and voice note into a shared Obsidian vault, and a neural network analyst every morning at 6:00 finds connections between the fresh and the old and puts the 3 strongest trading ideas for the day into the inbox. No analytics desk, no Bloomberg terminal, no Telegram chats with traders. Just a Mac Mini by the wall, an iPhone in the pocket, and 1 local Obsidian vault. And traditional quant funds keep entire teams of 8 people on salary for the same flow of insights, while his expenses are only subscriptions to Readwise, Whisper API, and N8N hosting. 6 pipelines process about 200 sources a day and close the monthly API bill at about $120. The Mac Mini itself stores the entire vault and keeps the neural network analyst running 24/7, and from the iPhone the owner drops any idea he hears on the go into a Telegram bot, and it lands in the vault inbox in just 30 seconds. The starting instruction that sits in the VAULT.md file at the root of his vault looks like this: "you are the AI analyst of a solo trader. you read his vault every morning at 6:00, find connections between fresh and old notes, and deliver 3 trading ideas he can verify in the hour before the market opens. pipelines: // Reader (pulls every article and highlight from Readwise, Twitter bookmarks, and Kindle into /notes) // Listener (transcribes podcasts through Airr and voice notes through Whisper, puts them in /notes) // Catcher (accepts any message from the Telegram bot and writes it to /inbox with a timestamp) // Connector (every night reads across the entire vault and updates the connection graph between 4,000 notes) // Briefer (at 6:00 AM writes a brief: 3 trading ideas for today plus the emerging thesis of the week, puts it in /inbox) // Mobile (lives in the iPhone, answers any question about the vault by voice, and confirms alerts while the owner is on the go). you wake the owner with a push notification only when a fresh note contradicts his active thesis or when 1 of the 3 morning ideas has a confidence score above 90%." This instruction immediately sets the role for the system and the limits of its autonomy. It knows it is supposed to connect new with old on its own. It knows it is supposed to prepare 3 trading ideas every morning on its own. It knows it connects the live trader only when a thesis is contradicted or an ultra-confident idea appears. → Reader pulls about 80 articles and highlights a day from Readwise, Twitter, and Kindle → Listener transcribes 4 to 6 podcasts a week through Airr and Whisper → Catcher intercepts all voice and text ideas through the Telegram bot, averaging 15 to 20 a day → Connector updates the connection graph between 4,000 notes every night, adding 25 to 30 new edges → Briefer puts a fresh brief with 3 trading ideas and the emerging thesis into the inbox at exactly 6:00 → Mobile answers any question about the vault by voice and confirms alerts right from the iPhone And only when a new note contradicts his active thesis or 1 of the ideas breaks 90% confidence does the orchestrator raise the owner with a push notification. And when the trader at that moment is driving to the gym or eating breakfast, the Mobile agent in his iPhone answers any quick question about the vault by voice: what he wrote about this ticker last week, which 3 sources support the idea of long NVDA, and what counter-thesis already sits in his notes. The trader makes the decision and sends the order before New York opens. The fresh brief from last Monday looks like this: "reader: 78 materials added over the weekend, 11 of them about semiconductors, 4 about energy, 3 about biotech. passing to connector." "connector: 27 new connections found between fresh materials and the vault, the strongest one is that the Goldman report from Wednesday matches the NVDA thesis you wrote 3 weeks ago." "briefer: 3 trading ideas for today: long NVDA (confidence 0.84), short Tesla at the close of the quarterly report (0.71), watch URI (0.62). emerging thesis of the week: the market is underpricing capex on data centers." "alert: your fresh note about long-term risk in semis contradicts the NVDA thesis. sending for review." In his work setup there is no cloud server, no team of analysts, and not even a Bloomberg subscription. At home sits a Mac Mini with a local Obsidian vault, on top run 6 N8N pipelines and a neural network analyst, and the same vault mirrors to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo trading setup on a second brain: $120 a month on the API, about $30,000 a month into the account, and between them 6 pipelines, 4,000 connected notes, and 1 iPhone in the pocket.

This Chinese guy built a Second Brain in Obsidian and every morning gets 3 trading ideas that brought him $180,000 in 6 months. Inside he runs a pipeline of 6 workflows on N8N that automatically pulls every read article, listened podcast, and voice note into a shared Obsidian vault, and a neural network analyst every morning at 6:00 finds connections between the fresh and the old and puts the 3 strongest trading ideas for the day into the inbox. No analytics desk, no Bloomberg terminal, no Telegram chats with traders. Just a Mac Mini by the wall, an iPhone in the pocket, and 1 local Obsidian vault. And traditional quant funds keep entire teams of 8 people on salary for the same flow of insights, while his expenses are only subscriptions to Readwise, Whisper API, and N8N hosting. 6 pipelines process about 200 sources a day and close the monthly API bill at about $120. The Mac Mini itself stores the entire vault and keeps the neural network analyst running 24/7, and from the iPhone the owner drops any idea he hears on the go into a Telegram bot, and it lands in the vault inbox in just 30 seconds. The starting instruction that sits in the VAULT.md file at the root of his vault looks like this: "you are the AI analyst of a solo trader. you read his vault every morning at 6:00, find connections between fresh and old notes, and deliver 3 trading ideas he can verify in the hour before the market opens. pipelines: // Reader (pulls every article and highlight from Readwise, Twitter bookmarks, and Kindle into /notes) // Listener (transcribes podcasts through Airr and voice notes through Whisper, puts them in /notes) // Catcher (accepts any message from the Telegram bot and writes it to /inbox with a timestamp) // Connector (every night reads across the entire vault and updates the connection graph between 4,000 notes) // Briefer (at 6:00 AM writes a brief: 3 trading ideas for today plus the emerging thesis of the week, puts it in /inbox) // Mobile (lives in the iPhone, answers any question about the vault by voice, and confirms alerts while the owner is on the go). you wake the owner with a push notification only when a fresh note contradicts his active thesis or when 1 of the 3 morning ideas has a confidence score above 90%." This instruction immediately sets the role for the system and the limits of its autonomy. It knows it is supposed to connect new with old on its own. It knows it is supposed to prepare 3 trading ideas every morning on its own. It knows it connects the live trader only when a thesis is contradicted or an ultra-confident idea appears. → Reader pulls about 80 articles and highlights a day from Readwise, Twitter, and Kindle → Listener transcribes 4 to 6 podcasts a week through Airr and Whisper → Catcher intercepts all voice and text ideas through the Telegram bot, averaging 15 to 20 a day → Connector updates the connection graph between 4,000 notes every night, adding 25 to 30 new edges → Briefer puts a fresh brief with 3 trading ideas and the emerging thesis into the inbox at exactly 6:00 → Mobile answers any question about the vault by voice and confirms alerts right from the iPhone And only when a new note contradicts his active thesis or 1 of the ideas breaks 90% confidence does the orchestrator raise the owner with a push notification. And when the trader at that moment is driving to the gym or eating breakfast, the Mobile agent in his iPhone answers any quick question about the vault by voice: what he wrote about this ticker last week, which 3 sources support the idea of long NVDA, and what counter-thesis already sits in his notes. The trader makes the decision and sends the order before New York opens. The fresh brief from last Monday looks like this: "reader: 78 materials added over the weekend, 11 of them about semiconductors, 4 about energy, 3 about biotech. passing to connector." "connector: 27 new connections found between fresh materials and the vault, the strongest one is that the Goldman report from Wednesday matches the NVDA thesis you wrote 3 weeks ago." "briefer: 3 trading ideas for today: long NVDA (confidence 0.84), short Tesla at the close of the quarterly report (0.71), watch URI (0.62). emerging thesis of the week: the market is underpricing capex on data centers." "alert: your fresh note about long-term risk in semis contradicts the NVDA thesis. sending for review." In his work setup there is no cloud server, no team of analysts, and not even a Bloomberg subscription. At home sits a Mac Mini with a local Obsidian vault, on top run 6 N8N pipelines and a neural network analyst, and the same vault mirrors to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo trading setup on a second brain: $120 a month on the API, about $30,000 a month into the account, and between them 6 pipelines, 4,000 connected notes, and 1 iPhone in the pocket.

Blaze

928,221 просмотров • 3 месяцев назад

THIS MAN HASN’T HAD A SINGLE ORIGINAL IDEA IN 8 WEEKS. CLAUDE HAS ALL OF THEM BEFORE HE WAKES UP he gave claude his obsidian vault on a saturday by monday it found a link between two notes written 6 weeks apart in different folders he turned that connection into his best-performing post his competitors are still organizing folders and writing morning pages and brainstorming in notion the only difference is one file called CLAUDE.md every note = fuel and every morning = synthesis and every week = ideas compounding faster than he can publish them this is not a tool anymore and this is not even an assistant this is a second brain that studied you for 2 months straight bookmark & like this or lose it forever

THIS MAN HASN’T HAD A SINGLE ORIGINAL IDEA IN 8 WEEKS. CLAUDE HAS ALL OF THEM BEFORE HE WAKES UP he gave claude his obsidian vault on a saturday by monday it found a link between two notes written 6 weeks apart in different folders he turned that connection into his best-performing post his competitors are still organizing folders and writing morning pages and brainstorming in notion the only difference is one file called CLAUDE.md every note = fuel and every morning = synthesis and every week = ideas compounding faster than he can publish them this is not a tool anymore and this is not even an assistant this is a second brain that studied you for 2 months straight bookmark & like this or lose it forever

leopardracer

27,938 просмотров • 3 месяцев назад

This is the easiest way to make $10k/month with organic affiliate and AI Arcads launched an ai ugc studio that lets you build an entire army of hyper-real AI actors Then you turn any static image into a high-quality video showcasing any product go to TikTok and make an account + warm it up using arcads you can run an entirely AI UGC account using the same character over and over, making it seem like an authentic TT page Mix the content up with slideshows and videos with the same character Here's the AI stack gameplan: - Claude to help you write scripts - Arcads to generate an image of an AI girlie that fits your product demographic Scroll tiktok and save + download every video / slideshow you see made by clippers promoting a product (there's literally loads) Your going to find an offer on whop for making money online or spirituality and target it towards girls feed all these videos you scraped into a custom google gemini gem trained to deconstruct hooks / angles for you for easy hook inspiration + ideas Deconstruct the hooks, put them into Claude and ask it to give you hooks for the same style of video put for your products your promoting For the videos do caption and reaction + showcase formats Generate the reactions using the character you made in arc ads then manually record the showcasing of the product or proof of the product working Also for caption generate a 8-10 second video you can put text over Include your CTA in the video for reaction style and captions for caption style Plus generate images with the same character and make slideshows directed to your product Now rinse and repeat this make multiple accounts with multiple different avatars and print

This is the easiest way to make $10k/month with organic affiliate and AI Arcads launched an ai ugc studio that lets you build an entire army of hyper-real AI actors Then you turn any static image into a high-quality video showcasing any product go to TikTok and make an account + warm it up using arcads you can run an entirely AI UGC account using the same character over and over, making it seem like an authentic TT page Mix the content up with slideshows and videos with the same character Here's the AI stack gameplan: - Claude to help you write scripts - Arcads to generate an image of an AI girlie that fits your product demographic Scroll tiktok and save + download every video / slideshow you see made by clippers promoting a product (there's literally loads) Your going to find an offer on whop for making money online or spirituality and target it towards girls feed all these videos you scraped into a custom google gemini gem trained to deconstruct hooks / angles for you for easy hook inspiration + ideas Deconstruct the hooks, put them into Claude and ask it to give you hooks for the same style of video put for your products your promoting For the videos do caption and reaction + showcase formats Generate the reactions using the character you made in arc ads then manually record the showcasing of the product or proof of the product working Also for caption generate a 8-10 second video you can put text over Include your CTA in the video for reaction style and captions for caption style Plus generate images with the same character and make slideshows directed to your product Now rinse and repeat this make multiple accounts with multiple different avatars and print

Pounds

32,407 просмотров • 7 месяцев назад

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

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

West Lord

24,679 просмотров • 1 месяц назад

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

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

marfin

20,684 просмотров • 1 месяц назад

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription.

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription.

CyrilXBT

46,087 просмотров • 1 месяц назад

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.

A CHINESE TRADER BUILT A SECOND BRAIN IN OBSIDIAN THAT GENERATES 3 TRADING IDEAS EVERY MORNING AT 6AM AND MADE $180,000 IN 6 MONTHS. No Bloomberg terminal. No analytics desk. No team of analysts. A Mac Mini by the wall. An iPhone in his pocket. One local Obsidian vault. Six N8N pipelines running 24/7, pulling every article he reads, every podcast he listens to, and every voice note he drops into a Telegram bot—directly into the vault. Every night, a neural network reads across 4,000 connected notes and finds the strongest connections between fresh information and old theses. Every morning at 6AM, a brief lands in his inbox: - 3 trading ideas with confidence scores - The emerging thesis of the week - Any note that contradicts an active position The system only wakes him up when a fresh note contradicts his thesis, or when an idea breaks 90% confidence. Everything else runs without him. The monthly bill: $120 in API costs. The monthly return: approximately $30,000 into the account. Traditional quant funds pay teams of 8 people to produce the same flow of insights. He pays $120 and a Mac Mini. The full system breakdown is in the article below. Bookmark this before you pay for a Bloomberg subscription. Follow CyrilXBT for every solo operator setup that changes what one person can build.

CyrilXBT

129,600 просмотров • 2 месяцев назад