logging

Detection quality is decided before the first alert, by what you logged and how you set the threshold. The scored answer derives both from the questions an investigator will ask.

The token is safely in the Keychain, and also in the crash log, the analytics payload and the app-switcher screenshot. Interviewers want the list of side doors, not the front door again.

Breadth first, then priority. The answer that scores follows one sensitive value through every copy the system makes and fixes the two that leak most.

LLM observability quietly becomes the largest copy of customer data in the company. The scored answer minimises what is captured, separates what must be kept, and treats trace stores as production data.

Connect task authority, evidence, dispatch attempts and observed effects. Learn what references, hashes and signed logs can establish, and test collection gaps without overcollecting sensitive data.

Separate a suspicious signal, a verified effect and a causal hypothesis. Then contain the real path, scope exposure and record what is still unknown.

Design records for identity, context provenance, authorization and actual effects. Include missing-event coverage and a protected way to retrieve evidence.

Preserve relevant evidence within its authorization boundary. Protect collection, record gaps and transformations, and explain what a checksum does and does not establish.