Tagged postmortems, named-failure-mode catalog.
Without a taxonomy, every incident feels novel and you can't tell whether anything is improving. The Failure Taxonomy workflow names the failure modes — hallucination, refusal-mismatch, retrieval miss, drift, prompt-injection, and so on — so you can count them, attribute them, and trend them. The taxonomy is what turns an incident from "weird thing that happened" into "the third hallucination this quarter."
The Failure Taxonomy workflow is the procedure for maintaining a written list of named AI failure modes, tagging every production incident against it, adding new failure modes to eval suites as part of the incident response, and reviewing the taxonomy on a regular cadence so it doesn't go stale.
The five questions on the readiness self-assessment that score this dimension are the five rungs of the procedure above. Yes on a question means the artifact named in that step exists on disk in your repo today.
This page is a thin first cut. Full procedural documentation — including reference DeepEval suite scaffolds, golden-set curation rubrics, and the audit-evidence checklist — lands in Phase 2 of the Institute build-out.
The free readiness self-assessment scores the Failure-Taxonomy workflow as one of six dimensions. Five minutes. Your weakest workflow is the one most worth fixing first.
Take the assessment →