Commentary

Nate’s take on AI in production, reliability metrics, and how engineering teams work.

Connect on-call interruptions, specialist demand, and recovery work to a concrete capacity decision using an on-call workload worksheet.

January 29, 20265 min read

Read validated architectures as a starting point for workload, recovery, and support testing, not a promise of automatic reliability.

April 2, 20254 min read

Compare detection, correlation, investigation, and automation using your incidents, review costs, and failure paths.

March 24, 20253 min read

Locate the delay, choose a bounded intervention, and measure recovery quality alongside elapsed time.

March 23, 20254 min read

Make a useful AI request without assuming that tool approval, anonymization, or a training opt-out settles every data-handling question.

January 8, 20253 min read

Separate incident coordination from mitigation authority, compare competing actions, and use a worksheet that preserves decisions and verification.

October 16, 20235 min read

Define who does the work, who decides, and who accepts risk so ownership remains useful during incidents and follow-up.

October 7, 20233 min read

Make AI-assisted routing and remediation accountable through visible evidence, meaningful overrides, and review of who bears the errors.

September 30, 20233 min read

Protect time away through explicit coverage, recovery policies, and realistic planning instead of relying on individual boundary-setting alone.

September 29, 20233 min read

Use interruption patterns and responder feedback to change paging, coverage, and recovery expectations when on-call work becomes unsustainable.

September 29, 20233 min read

Give teams clear service ownership, decision authority, and capacity to act on reliability evidence before the next incident.

September 28, 20233 min read