Explainable Agent Framework: Making AI decisions transparent
blaizedsouza · x · 2026-08-16
To address user and auditor questions about agent decisions, an Explainable Decision Framework is proposed. Core elements include capturing key decision points, recording option selection rationale, generating human-readable explanations on demand, supporting varied depths, and storing for review. The principle: an agent that cannot explain itself is hard to trust and improve.
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