Architecture-Systems

People often ask what it actually looks like day-to-day to have an AI agent manage infrastructure you depend on — not a chatbot you occasionally ask questions, but something closer to a project lead that reads your backlog, opens pull requests, and pings you when it needs a decision. Here’s the actual stack, the actual hardware it runs on, and the actual daily loop, not the marketing version. The setup, in one paragraph My home runs on Home Assistant, self-hosted, with the entire configuration in a self-hosted Git repo (Gitea, running on my NAS). Claude Code — an agentic coding CLI — has full read/write access to that repo and to a set of scoped tools (deploy/reload commands, a self-hosted issue tracker, some read-only APIs for other systems on my network). It does not have access to secrets files directly, cannot restart the core service without asking, and cannot touch a handful of centrally-important files without my explicit sign-off. Everything else — writing automations, fixing bugs, refactoring, documentation — happens largely on its own, inside guardrails I’ve built up over months. ...

The introduction post gave you the elevator pitch. This one is the wiring diagram — how a coding agent ends up running semi-persistently against real home infrastructure, how I talk to it from my phone on the other side of the planet, and what happens when a session runs for hours and hits a wall it wasn’t supposed to hit. It’s not a chat window. It’s a long-running process. The mental model that trips people up first: this isn’t “I open an app, type a question, get an answer, close the app.” The agent runs inside a coding CLI, and that CLI process needs to keep existing between the moments I’m actually typing to it — otherwise every session starts from zero, re-reading the whole repository to figure out what’s going on. ...