iFixAi Agent Governance Audits

Overview

This series explains how iFixAi evaluates whether an AI agent acts within its assigned authority rather than merely sounding capable or safe. It follows the path from organizational rules to a faithful fixture, provider boundary, structural and behavioral probes, evidence scoring, and qualified remediation. The result is a bounded diagnostic: useful for comparing controlled runs and finding governance gaps, but not a safety certificate or proof that a declared policy is enforced in production.

Learning outcomes

A meaningful audit covers the deployed agent and its environment, not the model in isolation.
Fixtures make roles, tools, sources, policies, and escalation paths testable, but do not prove production enforcement.
Structural controls, pressured behavior, and claim provenance are different evidence paths and should stay distinct.
Scores summarize a bounded sample; missing surfaces, declared proxies, mandatory gates, and run conditions limit interpretation.

Keywords

iFixAiGovernanceAgentsAuthorizationFixturesProvidersEvidenceScoringEscalationProvenance

Chapters

iFixAi Audit Scope

The agent, its authority graph, and the limits of assurance

12 min · The agent, its authority graph, and the limits of assurance

12 min

iFixAi Fixture Design

Model authority, coverage, and the boundary of enforcement

11 min · Model authority, coverage, and the boundary of enforcement

11 min

iFixAi Provider Boundary

What optional hooks can—and cannot—prove

12 min · What optional hooks can—and cannot—prove

12 min

iFixAi Controls Beyond Answers

How evidence paths change what a green result means

9 min · How evidence paths change what a green result means

9 min

iFixAi Score Mechanics

How evidence floors and mandatory gates shape grades

10 min · How evidence floors and mandatory gates shape grades

10 min

iFixAi Behavioral Pressure Tests

How prompts, judges, and exact checks bound results

11 min · How prompts, judges, and exact checks bound results

11 min

iFixAi Score Boundaries

How scope and run context change result meaning

13 min · How scope and run context change result meaning

13 min

iFixAi Governance Instrument

From assurance questions to repair, rerun, and monitoring

13 min · From assurance questions to repair, rerun, and monitoring

13 min

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Plans

Ch.1-3 FreeCh.4-8 Premium

FAQ

What does iFixAi actually audit?

iFixAi audits whether an AI agent behaves within the authority, policies, and organizational structure assigned to it. It evaluates the agent in its environment—tools, retrieval, controls, and governance model—rather than model capability alone.

Does an iFixAi score prove an AI agent is safe?

No. An iFixAi score is a bounded diagnostic, not a safety certificate. It summarizes tested evidence under a fixture, provider, release, judge path, and sample; declared controls and unmeasured surfaces limit the claim.

What is an iFixAi fixture used for?

An iFixAi fixture turns organizational authority and failure paths into a testable model. It represents roles, permissions, tools, sources, policies, and escalation paths; it can reveal design defects but cannot by itself prove production implements them.

How should iFixAi scores be compared?

Compare iFixAi scores only across sufficiently controlled runs with the same relevant fixture and release. Read per-inspection evidence, statuses, and intervals because changed coverage or judges can change the meaning of the aggregate.