How an executive knows an AI system works: benchmarks and statistical measurement, verification and formal assurance, calibration and abstention, observability and error attribution, interpretability, evidence-carrying artifacts and acceptance contracts.
Evaluation and assurance · 5 min read · with a concept loop
A passed AI test proves one narrow property, not the whole task. The obligation ladder shows what to verify, test, prove and never assume.
formal verificationevaluation and benchmarksrelease gatesaudit trails
Evaluation and assurance · 5 min read · with a concept loop
AI confidence scores are not probabilities. Calibrating them and building a cost-based rule for when to abstain is what makes an AI answer trustworthy.
uncertainty and calibrationevaluation and benchmarksrisk managementreliability
Evaluation and assurance · 5 min read · with a concept loop
A benchmark score answers one of three different questions. The history ledger keeps reset, path-dependent and search-selected evaluation claims honest.
evaluation and benchmarksrelease gatesautomated gradingrisk management
Evaluation and assurance · 5 min read · with a concept loop
A trace shows what happened, not what caused it. The causal proof ladder is the four checks that turn a plausible story into a demonstrated cause.
observability and debuggingreliabilityaudit trailsevaluation and benchmarks
Evaluation and assurance · 5 min read · with a concept loop
A readable AI explanation is not proof of a mechanism. The four-claim model shows what interpretability and steering evidence actually establishes.
interpretabilitysafety and red teamingevaluation and benchmarksobservability and debugging
Evaluation and assurance · 5 min read · with a concept loop
A passing research dossier is not proof. The bounded verdict ledger traces every claim to its source and states exactly where the checking stopped.
research due diligenceaudit trailsevaluation and benchmarksrisk management
Evaluation and assurance · 5 min read · with a concept loop
A fixed AI coding harness inside a versioned artifact loop can make work cumulative, but hierarchy alone does not yet prove better quality.
coding agentsagent runtimeself improving systemsevaluation and benchmarks
Evaluation and assurance · 5 min read · with a concept loop
A passing test, a signature and a benchmark score are different evidence types. The evidence contract binds each to one artifact before it counts.
release gatesaudit trailsevaluation and benchmarksdata provenance
Evaluation and assurance · 5 min read · with a concept loop
A passing benchmark score is not proof. The evaluation chain of custody defines, freezes, grades and gates the evidence behind an AI release decision.
evaluation and benchmarksautomated gradingrelease gatesaudit trails
Evaluation and assurance · 5 min read · with a concept loop
A signature proves who signed an AI system output, not that it is true. See what computational provenance and causal-state attestation can prove.
Evaluation and assurance · 5 min read · with a concept loop
A proof can compile and check while proving the wrong statement. The three-gate model shows what a formalization must clear before it is trusted.
formal verificationevaluation and benchmarksresearch due diligenceaudit trails
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