WhatA structured, searchable platform that ingests historical and ongoing technology failure reports (like RISKS Digest) and uses AI to classify, tag, and surface recurring failure patterns for engineering teams.
SignalCommenters describe how reading decades of accumulated failure reports in bulk caused clear failure stereotypes to emerge, fundamentally reshaping their mental models of technology risk — but the original archive is unstructured and its future is uncertain after its curator's death.
Why NowAgentic AI systems are introducing novel failure modes at unprecedented speed, while the institutional knowledge of technology risks sits in fragile, single-maintainer archives that are at risk of disappearing.
MarketEnterprise engineering and security teams at companies building safety-critical or AI-powered systems; $2B+ GRC/risk management market; competes with ad hoc internal postmortems and generic risk frameworks, but nothing structures historical cross-industry failure patterns.
MoatCurated dataset of decades of real-world failure cases, classified and enriched — this corpus is irreplaceable and compounds in value as new incidents are added.
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