Setting up robust approvals when an AI agent needs to deny product requirements necessitates a human-centric oversight model. The AI primarily serves as a recommendation engine, flagging requirements that violate predefined criteria such as technical feasibility, resource constraints, or strategic misalignment. When the AI recommends denial, it triggers an automated escalation workflow to designated human approvers, typically senior product managers or architects, who are then responsible for reviewing the AI's detailed rationale, overriding or confirming the denial, and providing feedback to refine the AI's decision-making logic. Crucially, a comprehensive audit trail must meticulously log every AI recommendation and subsequent human decision, ensuring accountability and facilitating continuous improvement of the AI model. This structured approach ensures that while AI optimizes initial screening, final decisions always reside with human accountability and expertise.