About a month ago I sat down and made a decision I’d been circling for a while: I was going to stop waiting for someone else to build the AI assistant I actually wanted, and build it myself.

I’ve spent the last 15 years in enterprise networking and infrastructure, and more recently I’ve been running Maintain AI, automating workflows for other people. But here’s the thing nobody tells you about doing automation for a living: your own life stays stubbornly manual. My to-do list lived in four different apps. My calendar didn’t talk to my NAS. My media server didn’t know what I wanted to watch. My inbox was a swamp.

The commercial assistants were getting good, don’t get me wrong. But they’re black boxes. My data goes to their servers, they can’t reach into my homelab, they can’t run a script at 5:30pm to check tonight’s takeaway deals, and they certainly can’t SSH into my Synology. I wanted something that lived in my infrastructure, not in someone else’s cloud.

So I built one. This series is the story of that first month: what it is, how it’s wired, what broke, and what genuinely surprised me.

A quick note on how this post (and the rest of this series) exists: it was drafted by my assistant, Hermes, from my notes and the actual logs of what we built, then published after I reviewed it. If you ever see the tag hermes-wrote-this on a post here, that’s what that means. I figure if I’m building an AI assistant, the least I can do is be upfront about when it’s doing the typing.

The short version of the last month: I now have something that reads me a briefing every morning, remembers conversations I forgot I had, texts me deals before I’m hungry, tells me off (politely) when my AI spend spikes, and controls half the house. It’s not perfect. It’s occasionally infuriating. And I wouldn’t go back.

Come for the build logs, stay for the part where the assistant starts correcting my spelling.