AI Context Governance: From Test Results to Production Controls
Read OriginalTL;DR AI context governance turns evaluation findings into controls over evidence, context assembly, and consequential actions. Preserve decision-critical facts through retrieval and summarization, distinguish source authority from access permission, and bind recommendations to the policy and target state they evaluated. Keep authorization outside the model. A passing evaluation supports a release
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