How to evaluate incident-response agents
Build repeatable cases and check recovery independently, with a runnable Python grader.
Guides, news and explanations about AI and reliable systems.
Build repeatable cases and check recovery independently, with a runnable Python grader.
How Herdr keeps coding sessions available while you detach, and what changes when its server restarts.
Separate a completed task from evidence that the underlying risk was reduced.
Evidence can split a 5 Whys investigation into several contributing causes. A concurrency example shows how to turn those explanations into useful tests.
Conflicting restart instructions show where a source-backed notebook helps: finding the relevant passages, dates and exceptions for the runbook owner.
A rollback exception tests whether Opus 4.6 preserves decisive evidence across a long session, and whether the resulting answer arrives in time to help.
A timed-out scaling request needs a durable record and destination-state checks. Reusable operational skills need to recover unfinished work as well as start it.
Disturbed nights, specialist help and cleanup consume capacity beyond the primary shift. A workload worksheet connects that demand to staffing and delivery plans.
An error-budget hold needs a route for an urgent repair. Fresh measurements, artifact-specific exceptions and recovery criteria determine how that route works.
A reference design for duplicate deliveries and partial API success, with durable incident identifiers and summaries drawn from the resulting record.
Regional failures can disappear in fleet averages. Grafana queries, population labels and linked traces help responders find the affected requests.
A reusable prompt connects observations, competing explanations and the next read-only check, so an incomplete record can still support useful investigation.