The Coe Lab
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Building The Coe Lab

April 1, 20265 min read

The story behind building a personal technology laboratory.

How I built a comprehensive homelab infrastructure with AI integration, automated monitoring, and self-hosted services.

The Coe Lab started as a simple idea: what if I could build a personal technology laboratory that combines infrastructure, AI, and automation into a cohesive system? Six months later, here's what I've built.

Everything runs in Docker containers on a Linux server with flexible storage virtualization, application hosting, and container management. Key benefits:

What makes The Coe Lab different is the AI layer that ties everything together. OpenClaw acts as the central nervous system:

Every hour, OpenClaw checks:

Results are posted to Discord's #TCL channel. If something's wrong, I know immediately.

Every 30 minutes, the media manager:

On the first run, it cleaned up 10 dead torrents and triggered searches for 12 movies and 5 TV shows.

My Windows gaming PC (LenovoGaming) runs OpenClaw Node for browser automation. If it goes offline:

This has saved me multiple trips to the basement to manually reboot the machine.

The AI assistant needs context to be useful. Neo4j stores:

This allows conversational queries like "What's the status of the website project?" or "When is Jeni's birthday?" with accurate, contextual answers.

The Coe Lab website (thecoelab.com) serves multiple purposes:

Built with Next.js 14, TypeScript, and Tailwind CSS, deployed as a static export to Nginx.

If I do something twice manually, it gets automated. This applies to media management, health checks, backups, and even reboots.

Systems should recover from failures automatically. The node reboot workflow is a perfect example—no human intervention needed.

Everything is monitored and logged. If something breaks, I want to know why. Grafana dashboards show trends over time, not just current status.

Every service, script, and configuration is documented in markdown. Future-me (or anyone else) should be able to understand how things work.

Authelia protects all external-facing services. Tailscale provides encrypted remote access. Internal services don't expose ports unnecessarily.

The roadmap includes:

Building this lab has taught me:

If you're building your own lab or have questions about any of these systems, I'm happy to share what I've learned. Reach out via the contact page or connect on Discord.

The Foundation: Docker on Linux

Core Services

The AI Integration Layer

Memory Architecture

Website & Public Presence

Key Design Principles

What's Next

Lessons Learned

Building The Coe Lab | The Coe Lab