AI assistance disclosure: This article was drafted with the help of Claude. All technical content, design decisions, code references, and screenshots reflect production systems I designed and operate at airCloset; the prose was revised by me prior to publication.
Hi, I'm Ryan, CTO at airCloset.
In Part 1, I walked through the four monitoring axes (application / infrastructure / CI / LLM) and the deliberately different shape each one ends up in. That's the write-side of the observability stack, more or less wrapped up.
But shaping the write side isn't the end of the story. The moment production data flows through the stack, you have to block the path PII can take to slip in — and that's true with or without AI. It's the kind of classic observability problem where, if you cut corners, you walk straight into a leak incident.
Historically, the set of people who could read logs mostly overlapped with the set who could read the DB. For engineers with DB access, logs weren't an additional path to personal data — which put log-side defenses in a position where hardening them didn't meaningfully move the overall defense line for most organizations.
