How do I satisfy the NIST AI RMF explainable-and-interpretable characteristic for an LLM agent?

To satisfy the NIST AI RMF explainable-and-interpretable characteristic for an LLM agent, organizations must integrate explainability into their risk-management culture and ensure mechanisms exist to log decisions and trace AI behavior.

• Integrate Trustworthy AI Characteristics: A risk-management culture should be in place where characteristics of trustworthy AI, including explainability, are integrated into organizational practices. This falls under the GOVERN function of the NIST AI RMF.
• Log Decisions and Trace AI Behavior: Implement mechanisms to log every AI decision and trace AI behavior. This is a concrete implementation of the MEASURE function, specifically NIST-MEASURE-2.8, which requires transparency and accountability mechanisms.
• Ensure Forensic Readiness: The system must be able to reconstruct the full sequence of events, including what the agent saw, decided, and the tools it called, to support incident response, compliance verification, and internal review. This requires immutable, queryable records that preserve decision context.
• Implement Comprehensive Telemetry: Telemetry should be produced by construction at every chokepoint, ensuring that no action or decision goes untraced. This contributes to Observability within the ORCHIDEAS framework.
• Maintain Tamper-Evident Audit Logs: To prevent attackers from deleting or modifying audit trails, implement tamper-evident audit logs using write-once storage, signed entries, or append-only ledgers, and ship them out-of-band to a SIEM with separate access controls. This addresses log tampering, a MAESTRO threat relevant to Observability.