How I Built a Personal Knowledge System with Obsidian, AI, and Plain Text

Alternatively titled: How plain text, coding agents, and a little imagination transformed my work life.

Hello fellow datanistas!

Ever feel like you’re drowning in meetings, projects, and random documents—and your brain just can’t keep up? I’ve been there. Managing twelve people across two teams, each juggling multiple projects, forced me to rethink how I handle information. What started as a simple experiment with Obsidian and plain text turned into a system that changed how I work (and think).

This post is my honest, behind-the-scenes look at how I built a personal knowledge management (PKM) system using Obsidian, plain text, and AI coding agents. My hope is that sharing my process—warts and all—will inspire you to experiment with your own workflow, no matter your technical background.

When I first set out to improve my PKM at work, I faced a familiar dilemma: stick with the usual suspects (Confluence, OneNote), or try something new. I chose Obsidian and, more importantly, I chose plain text. At the time, it felt like a nerdy preference for graphs and open formats. In hindsight, it was a lucky break—plain text turned out to be the perfect foundation for integrating AI agents down the line.

My system revolves around a few core note types: monthly bullet journals, structured meeting notes, dossiers for people I work with, and project control towers. Everything is linked, everything is searchable, and—crucially—everything is in a format that both humans and AI can process.

Ingesting information used to be a slog. Now, AI skills handle the heavy lifting: parsing meeting transcripts, summarizing documents, and even extracting structure from messy Excel files. I’ve written Python scripts for everything from converting Word docs to plain text, to generating PowerPoint decks from Markdown. Each script declares its dependencies inline, so I never have to worry about environment issues or ‘works on my machine’ headaches.

The real magic is in maintenance. When I hit a context block—forgetting a detail about a person or project—I trigger a sweep. My coding agent updates notes based on source material, always quoting the original. I stay in the loop for verification, but the system does most of the grunt work. Retrieval practice and periodic reviews keep the vault trustworthy.

Sharing is intentional. I curate what gets published, whether it’s to Confluence, GitHub, or Google Docs. The agent creates publishable versions, and I review before sharing. The workflow isn’t perfect (I still wish I could ingest cloud docs by URL), but it’s reduced my knowledge management overhead from 30-40% of my time to less than 10%.

If you’re curious about the technical details or want to try some of my agent skills, I’ve published a few (like html-presentations and gh-activity-summary). The bigger picture: this system lets me offload repetitive work to AI, freeing up time for deeper thinking and more meaningful interactions. It’s not a prescription—just an invitation to experiment and find what works for you.

For the full technical breakdown and scripts, check out the original blog post: Mastering Personal Knowledge Management with Obsidian and AI.

Plain text plus coding agents is a powerful, future-proof combo for managing knowledge at work. The best system is the one you actually use—and document.

How do you keep track of everything at work? Have you tried building your own PKM system, or are you still searching for something that fits? I’d love to hear what’s worked (or not) for you.

If you found this helpful, check out the full blog post for scripts, technical details, and more stories. And if you’re experimenting with your own PKM setup, hit reply—I’d love to swap notes!

Cheers,
Eric