Ai

With the new SOC structure and dashboard built, I decided to take on a bigger project: integrating Kimi as a security AI analyst. Its role covers reporting on alerts, examining logs, judging whether something is a false positive, and auditing continuously. It is built in phases, and each phase needs extensive validation before the next one starts. The problem The SOC we built catches things. Seven log sources into Loki, 36 detection rules, alerts routed to my phone by severity, one Grafana dashboard over all of it. ...

The council worked. One request went to Claude, Codex and Kimi, they answered independently, and nothing touched the lab without a human approval bound to a hash of the exact plan. It also lived entirely in a terminal, which meant that to approve a run I had to type a run id like hc-20260822-6fbfa5 and then re-type the original 350-character request verbatim, because resume rebuilds the context pack from it. Get one character wrong and you have quietly changed the inputs the agents were judged on. ...

I have three coding agents with access to this lab. Claude Code does most of the building. Codex reviews and runs the scans. Kimi audits. Until this week they had never exchanged a word — each got its own context, its own session, and its own chance to be confidently wrong with nobody checking. So I built a thing that makes them work one request together, and put a human approval gate in front of anything that changes the lab. ...

My homelab has picked up a lot of moving parts this year, and several of them are now LLMs. Claude Code runs natively on the box and does real work against real infrastructure — containers, reverse proxy config, monitoring, the lot. That’s genuinely useful. It also creates a trust problem I hadn’t had before. The problem is simple to state: the same agent that makes a change also writes the summary explaining why the change was safe. That’s convenient. It is not independent verification. If the agent quietly skips a validator and then reports “config validated”, I have no signal at all. The report is the evidence, and the thing that wrote the report is the thing being checked. ...

Claude Code is the main LLM running my homelab. It builds, debugs, and documents most of what happens on the Debian VM. But I wanted to try other models — and give the CLI tools a shared backend — without wiring up a different SDK and API key for every provider. So I put a gateway in front: one endpoint, many models. Claude stays the main driver; everything else is now one config line away. ...