GROK BOT WIRED INTO OBSIDIAN JUST CHEWED THROUGH 4,200 NOTES IN 9 MINUTES AND FOUND 3 IDEAS I ALREADY FORGOT I HAD
X amateurs still paste prompts into a chat window and copy the answer back by hand while pros give the agent write access to the vault and walk away
your second brain is a graveyard 4,200 files, 380 orphans nothing links to, a search bar as your only tool
the exact architecture:
point a Grok swarm at 1 vault folder through an MCP filesystem server with read and write, so the agents stop guessing from context and start reading every daily log, every clipped thread, every dead draft from 2024
force one instruction: find every concept sitting in 3+ notes with no [[link]] between them, build the MOC, wikilink both directions 9 minutes, 214 new links, 38 orphans pulled back in
make it write markdown back into the vault instead of dumping to chat, so tomorrow the swarm reads what it wrote yesterday and compounds instead of resetting when you close the tab
that's the whole loop read the vault, write to the vault, compound
the complete automation script
I spent 3 years taking notes I never read, the bot read all 4,200 in 9 minutes
🚨 BREAKING: You can run Claude Code completely free now.
No API bills.
No rate limits.
No data leaving your device.
Just Claude Code running locally fast, private, and 100% yours. Here’s how to set up Claude Code on your own machine (free + fully private)
For guide: Local AI Coding Setup: Free Claude-Like Agent (Ollama + VS Code)
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🚨 BREAKING: Someone just made 70B parameter models run on a single 4GB GPU.
It's called AirLLM. No quantization. No distillation. No pruning. Just raw 70B inference on hardware that costs less than a dinner.
You can even run Llama 3.1 405B on 8GB VRAM.
Here's how it works:
→ Decomposes the model layer-by-layer
→ Loads only one layer into GPU memory at a time
→ Runs inference, moves to the next layer
→ Prefetches the next layer while computing the current one
→ Supports 4-bit and 8-bit compression for 3x speed boost
No cloud API. No $10K GPU. Just pip install airllm and go.
Here's the wildest part:
It supports almost every major model — Llama, Qwen, Mistral, ChatGLM, Baichuan, InternLM — and it auto-detects the model type. One line of code to load. One line to generate.
Works on Linux, macOS (Apple Silicon), and even Google Colab free tier.
Your old gaming laptop can now run the same models that needed an A100.
100% Open Source. Apache 2.0 License.
Who is a Full-stack AI Engineer?
Production-grade AI systems demand a deep understanding of how LLMs are engineered, deployed, and optimized.
Here are the 8 pillars that define serious LLM development:
Some more practice. Was my first time drawing Jayce and I really struggled lol, he took me way longer than the rest
#arcane#jayvik#Sevika#silco#arcanetwt