Failure PatternsIn build

Interactive Failure Pattern Map

Recurring failures become permanent guardrails.

Failure Patterns in the proof lifecycle.

The Failure Pattern map records recurring ways AI-built software fails — false-green results, missing evidence, weak authorization, demo-to-real gaps, approval confusion, stale proof — and the research response each one triggers.

Interactive Failure Pattern MapInteractive illustration · sample data
An illustrative map of recurring failure patterns feeding into research responses. Selecting a failure pattern illuminates its response path and shows the evidence needed and the resulting safeguard. The central app is illustrative, not a live customer system.

Recurring failure patterns

AI-built app
illustrative

Research responses

Guardrail added
Evidence required
Checker review
Gate / authorized review
Benchmark added
Future regression check

Failure · False-green result

Checks pass but the claimed user or system outcome is not proven.

Evidence needed

Human-opened outcome witness

Resulting safeguard

Benchmark added

Failures become guardrails.

Relation to the Evidence Lab.

Failure Patterns feed back into the Evidence Lab: each pattern becomes a new evidence requirement, a benchmark, or a guardrail that future work must pass.

What is not claimed.

  • Interactive illustration · sample patterns, not incident telemetry.
  • The central app is illustrative, not a live customer system.
  • A recorded pattern is a research response, not a security claim.