inversion-mental-model-state-machine-skill

Risk inversion is a protocol that maps and inverts failure modes to ensure robust AI recommendations. It requires explicit goal definition, failure-path enumeration, and ranking to establish defensible guardrails and recovery plans.

To apply a state machine for risk analysis, execute a five-state inversion workflow: Goal Framing, Inversion, Ranking, Guardrail Conversion, and Recommendation Assembly. This process systematically converts identified failure modes into enforceable guardrails.

Generate a failure-map.md artifact by defining explicit goals, inverting them to identify major failure paths, and converting ranked risks into guardrails. This captures assumptions and recovery steps for audit and defensive strategy.

Yes, you can use inversion protocols for AI agent safety. The workflow converts defensive strategy into mandatory artifacts, ensuring decision recommendations are preceded by structured risk analysis and recovery plans.

The best way to enumerate failure paths is through structured inversion. After ranking these failure modes, convert the highest priority risks into explicit guardrails to produce a final, defensible recommendation.