AuditLoop
Business-facing AI reliability work, not a raw research link
AuditLoop is the interpretation layer between Toppy's calibration research and practical delivery: it defines what to measure, what to report, and what a small team can operate after launch.
Definition
What AuditLoop is
AuditLoop is a practical reliability workflow for model-mediated operations. It turns model behavior into testable evidence, failure-mode notes, and escalation rules that can be reviewed by operators.
What it measures
- Task boundaries, refusal behavior, confidence, and ambiguous cases.
- Failure modes, severity, recurrence, and operational impact.
- Human escalation points and evidence needed for review.
What it produces
- Evaluation criteria and test cases.
- Failure-mode report with unresolved risks.
- Escalation map and implementation priorities.
Research link
Where the arXiv paper fits
The overconfidence and calibration paper is theoretical background, not the delivered product by itself. AuditLoop uses that line of reasoning to make practical questions explicit: when a model sounds stable, where can it still be miscalibrated, and what evidence would let a team notice?
Delivery
What an engagement can look like
Evaluation sprint
Short, bounded review of one model-mediated workflow, ending in test cases, failure modes, escalation rules, and unresolved risks.
Reliability review
Deeper review for teams preparing a launch, vendor decision, governance discussion, or internal automation rollout.