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THIS DEVELOPER TURNED A $599 MAC MINI AND $110 OF EXTRA HARDWARE INTO A PRIVATE AI COMPUTER THAT FITS IN A BACKPACK 00:49 he takes the complete setup out of the bag, connects it to a nearby screen and restores the same desktop, files and running tools in less...

30,550 görüntüleme • 1 ay önce •via X (Twitter)

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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

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58,186 görüntüleme • 1 ay önce

THIS GUY IS WALKING INTO LOCAL SHOPS WITH A MAC MINI IN A HARD CASE AND WALKING OUT WITH $1,200 CHECKS FOR INSTALLING AI THAT RUNS WITHOUT THE INTERNET I had to rewatch this twice because the business model is so stupidly simple my brain kept looking for the catch. He shows up. Plugs in a Mac Mini. Installs a private AI network running entirely on Ollama. The whole thing is done in under an hour. Zero cloud dependency. No API bills. No monthly charges bleeding the client dry. The shop owner gets a local AI system that works even if the WiFi dies, and this guy walks out with $1,200 for an installation that takes less time than a long lunch. The hardware costs $1,300. One deployment and the machine is paid for. Then he locks in a $149 monthly retainer for support, which means every client after the first is pure margin stacking on top of recurring revenue that compounds every single month. Most people hear "AI business" and think they need to build a SaaS platform or learn to code or raise funding from someone. This guy skipped all of that and went straight to walking into physical stores with a box under his arm. This is not going to scale to a billion dollar company. Obviously. But a solo operator clearing $5-10K a month from local installs while everyone else is still arguing about which LLM is best on Twitter is the kind of quiet hustle that does not make headlines until someone does a breakdown of their year-end numbers. The surface area of what AI can do right now is expanding faster than anyone can map it. One guy is doing local hardware installs. Another is generating AI personas that pull five figures a month. Someone else is running AI video pipelines off a laptop. Same wave of tools. None of them competing with each other. Hit play. Watch him unbox the setup and walk through the numbers. Then tell me you could not do this in your city by next Friday.

Framez

923,112 görüntüleme • 6 gün önce

A DEVELOPER CONNECTED CLAUDE CODE TO OBSIDIAN SO HIS AI AGENT WOULD STOP FORGETTING THE PROJECT EVERY MORNING. Every coding session used to start the same way. Claude would understand the repo, fix the bug, explain the architecture, and then the moment the session ended, all of that context disappeared. Same codebase. Same decisions. Same architecture. Same mistakes repeated again. So he added a memory layer. Instead of treating Claude Code like a smart terminal, he connected it to a local Obsidian vault through MCP. Now Claude can read the repo, open the vault, create notes, link concepts, and write important decisions back into the system. When it studies the codebase, it does not just answer once and forget. It creates notes for the major services, maps how the architecture works, links auth to the database, connects APIs to storage, and records why certain migrations or design choices exist. Obsidian becomes the project graph. Now when he asks why something was built a certain way, Claude does not guess from the current prompt. It reads the decision notes. When he starts a new branch, Claude checks the active context file. When the work is done, it updates what changed, what is blocked, and what the next agent needs to know before touching the repo. That is the real loop: read context, write code, capture decisions, update memory. Most people are still using AI coding tools like disposable chat windows. Ask, patch, close, forget. This setup turns Claude Code into infrastructure. The repo gets a memory layer that survives every session, and multiple AI agents can work from the same project map without stepping on each other. The unlock is not better prompting. The unlock is giving the agent somewhere to remember what it already learned.

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