My Obsidian Vault Has Become Sentient (Well, Almost)

I’ve spent years using Obsidian for everything from quick notes to complex project management, and somewhere along the way, I decided my vault needed to do more than just sit there looking pretty. Today, my setup has evolved into something that feels almost alive - a system that runs every minute in the background, processing my scattered thoughts, organizing tasks, conducting research, and even writing synthesis documents without me lifting a finger. This isn’t just some basic automation - it’s a full AI-powered knowledge management system I built with Claude Code.

The problem that drove me to this solution was one I’m betting most of us face: the friction between capturing ideas and actually doing something with them. I’d jot down quick thoughts in my “Scratch.md” file with intentions like “TODAY: Follow up on that client email” or “RESEARCH: How Kubernetes handles pod networking,” but these would just sit there, lost in the noise of daily work until they became completely irrelevant.

I decided to solve this once and for all with a Ruby-based orchestrator that turns these scattered intentions into actionable work. The system watches for specific keywords in my scratch file and automatically triggers Claude Code to process them. It runs every minute via Keyboard Maestro, quietly transforming my digital mess into organized knowledge.

The architecture isn’t particularly complex, but it’s effective. I have a shell wrapper that gets called by Keyboard Maestro, which in turn fires up a Ruby automation scheduler. This scheduler loads rules from a YAML configuration, manages concurrent processes, and handles both keyword-triggered and scheduled tasks. The real magic happens through Claude Code integration, which provides everything from grammar correction to research document generation.

When I write something like “TODAY: Call the dentist about appointment” in my scratch file, the system detects the keyword during the next scan, extracts the content, corrects my grammar (because I type like a caffeinated squirrel), and adds it to today’s daily note with a timestamp. For research requests, it triggers a comprehensive process that searches the web and my vault, creates a structured document, and links it properly within my knowledge graph.

Beyond just reacting to keywords, the system also runs scheduled tasks. Every weekday at 9 AM, it cleans up duplicate tasks and stale items from my daily notes. Every 90 minutes, it analyzes my work tasks and updates priority analysis. And on demand, it combines existing notes into new insights through research synthesis.

The heart of the system is the ClaudeClient class that interfaces directly with Claude Code. This seamless integration means my vault can leverage Claude’s reasoning capabilities for everything from simple grammar correction to complex research synthesis. I spent way too much time on the process management and concurrency aspects, but it was worth it - the system handles multiple automation rules running simultaneously through a sophisticated locking mechanism.

This automation system has fundamentally changed how I interact with my knowledge base. Before, ideas would get captured but rarely acted upon. Research requests would pile up. Daily notes became cluttered with duplicate tasks. Now, thoughts flow seamlessly from quick capture to structured notes, research happens automatically while I focus on other work, and my vault actively helps me think by creating synthesis documents.

Here’s a real-world example: I’m in a meeting and quickly jot down “RESEARCH: GraphQL federation patterns for microservices.” Within minutes, the system has extracted this, triggered a research process, and by the time the meeting ends, I have a comprehensive research document waiting for me, properly linked and categorized.

I’ve built in comprehensive error handling and resilience features; the system includes atomic file operations to prevent corruption, graceful degradation when Claude Code is unavailable, automatic retry logic for transient failures, and detailed logging for debugging. It integrates with Keyboard Maestro, Obsidian (through native file-based integration, no plugins required), Claude Code CLI, and even my company’s Bitrix24 task management system.

The beauty of this system is its modularity. You could start with just the TODAY processor and gradually add more sophisticated automation rules. The key components you’d need are a trigger mechanism, Claude Code CLI for AI processing, a rule-based processor, and file-based integration with your knowledge management system. The entire thing runs locally, requires no cloud services beyond Claude Code, and gives you complete control over your automation logic.

I’m continuously expanding the system’s capabilities with smart tagging, meeting integration to process transcripts and extract action items, a research pipeline that automatically follows up with related questions, and synthesis triggers that detect when enough material exists to create synthesis documents.

This system represents a shift from knowledge management to knowledge automation. Instead of manually organizing and connecting information, my vault actively participates in my thinking process. The combination of Claude Code’s reasoning capabilities with local automation creates a personal AI assistant that understands my specific knowledge base, writing style, and workflow preferences.

The total time investment to build this system was about 3 days of focused development, but it saves me hours every week and has fundamentally improved the quality of my knowledge management. That’s the kind of productivity multiplier that makes you rethink what’s possible when you combine the right tools with thoughtful automation. I spent years trying to make my knowledge management system work for me, but I was always the one doing all the work. Now, it feels like I have a partner in the process; my vault isn’t just a passive container anymore - it’s an active participant in my thinking.