Exploratory AI Systems with Deferred Evaluation, Priority-Guided Reexamination, and Minimal-State Resume ; Rule-Compliant Flow Architectures for High-Cost Verification, EDA Exploration, and Distributed Orchestration

This submission presents an implementation-facing architecture for exploratory AI systems under high-cost verification, delayed evaluation, and constrained restoration. It integrates deferred evaluation, priority-guided reexamination, minimal-state resume, selective irreversible evaluation, and frontier-based restoration into one control framework. The paper positions these mechanisms as a technical branch of a broader irreversible-loss-prevention architecture for AI products and enterprise systems.