Learning from failure
Language agents may succeed on first exposure while failing to improve under repeated failure and feedback.
Evidence: E-P02-3600. Attacks: leakage, stronger baseline, scoring bug, reproduction failure.
Public Registries
These registries are intentionally small. They make the public layer machine-readable without exposing private product code, private finance execution, customer data, or unpublished commercial orchestration.
Downloads
Language agents may succeed on first exposure while failing to improve under repeated failure and feedback.
Evidence: E-P02-3600. Attacks: leakage, stronger baseline, scoring bug, reproduction failure.
High-risk AI action should require a warrant and receipt closure before it earns action credit.
Evidence: E-PCA-NOGO-001, E-DEMO-RECEIPT-001. Attacks: false no-go, missing receipt, credit leak.
Adaptive systems need observable relations, constraints, control debt, and evidence half-life.
Evidence: E-RO-PUBLIC-001. Attacks: missing relation, unmeasured debt, transfer failure.
Safe physical AI should not convert detector confidence directly into action under degraded evidence.
Evidence: E-P20-SYNTH-001, E-P20-PUBLIC-LOG-001. Attacks: independent dataset failure, baseline underfit.
Reading Rule
Each entry is expected to survive three questions: what is the exact claim, what evidence supports it, and what would make it narrower, false, or incomplete? When an attack succeeds, the correct response is not defensiveness; it is a boundary update, an artifact fix, or a new negative result.