GPT-6 Astra Support Ticket Deflection: The Proof-First Playbook

Effective AI support deflection should be measured as verified resolution rather than chat abandonment, requiring a correct permitted answer or action, no human takeover, and no same-intent customer return within 72 hours. The proposed GPT-6 Astra workflow separates model reasoning from authorization by using deterministic eligibility gates, verified retrieval tools, strict JSON action plans, constrained executors, independent policy critics, and auditable outcome events. It recommends beginning with low-risk, fact-verifiable cases such as delivery-status updates, applying conditional controls to SSO recovery, and automatically escalating sensitive scenarios including cancellations, billing disputes, fraud, legal matters, ownership changes, and security risks. The framework emphasizes that models must not invent customer facts or enforce their own policies, while application code should control permissions, evidence requirements, tool access, and human approvals. Costs should include more than model tokens, and performance should be segmented by intent and risk using metrics such as reopen rates, handoff quality, customer satisfaction, and reviewed samples of supposedly resolved cases.

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