GPT-6 Astra Knowledge Base Best Practices: Proof First

Reliable enterprise knowledge bases require governance before retrieval, with explicit source authority rankings that prioritize signed customer addenda and current policies over archived, draft, or informal materials. The proposed GPT-6 Astra workflow uses metadata filters for status, access, region, audience, ownership, and effective date; binds answers to authorized evidence with document-level citations; and requires abstention or human escalation when evidence is missing or current sources conflict. It distinguishes retrieval quality from answer faithfulness through separate evaluation measures for source recall, citation precision, claim support, conflict handling, and abstention, using high-value test questions that include superseded policies, regional exceptions, and no-answer cases. Long context windows and File Search are presented as investigation and retrieval tools rather than substitutes for authority decisions, permissions, or review. The approach also recommends maintaining auditable manifests and evidence traces, controlling costs through targeted retrieval and routing, and requiring accountable human review for high-risk domains such as legal, medical, financial, privacy, and incident-response work.

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