Homelab

Running notes on things I’ve hit, fixed, or found worth remembering.

My house is full of automation that never told me anything — until I gave it one push bus. The first thing I taught it to do was warn me before Claude Code cuts out mid-task.

I set out to answer a simple worry — is someone trying to get into my server? — and found the scarier question underneath it: if they did, would I even know? My front door was solid. The inside had an alarm with the wires cut, a web terminal sitting on the open internet, and no floor under the blast radius. Here’s the audit, and the three things I fixed.

Parliamentary roll-call votes are public, machine-readable, and almost completely unread. I built a thing that scrapes them, distills each decision into one plain-language question, shows which party voted which way, and lets you register whether you agree — then puts your answer next to how parliament actually voted. The rule that keeps it honest: the AI writes the summary, but it never decides a fact.

An AI agent on a scheduled idle walk through my notes pointed out that I’d built the same architecture three times — at work, in my homelab, and in my second brain — and that the third copy was missing the part that makes GitOps work. It was right. So we shipped the missing piece the same day.

I asked Claude Fable 5 to help me self-host a dashboard for my own Claude usage. Halfway through, its dual-use safety measures flagged the conversation and downshifted me to Opus 4.8. Nothing I did was wrong — the request just had the shape of something that is. That gap, between what a thing looks like and what it’s for, turns out to be the whole story.

A rejection isn’t actionable data. So an n8n workflow now extracts skill demand from live job listings, diffs it against what I can prove, and renders the gap as a dashboard — deployed like everything else here: via git push.

A farm robot is replacing pesticides with UV light at night. The clever part isn’t the robot — it’s the darkness. Here’s the home version, and the honest scope of what it can and can’t do.

Zero-shot voice cloning with XTTS-v2 on a CPU-only k3s node: 26 seconds of phone audio in, a cloned-voice audiobook out — and an honest verdict from the bedtime jury. Every manual step, including the ones that went wrong.

I gave my markdown knowledge base a nightly gardener — an AI that finds orphan notes and missing links and fixes them, every change a reviewable git commit. The fun part was the Kubernetes wall I hit on the way.