[Foundations] Relational Control: Why Execution Must Be Regulated Before It Occurs

This paper introduces relational control as a foundational requirement for stability in interactive AI systems. Current AI systems implicitly treat execution as permitted by default once inference is completed. This paper argues that many systemic instabilities — including over-execution, recursive amplification, mutual interference, and evaluation inconsistency — are structural consequences of this assumption. The paper establishes: execution-as-default as a structural instability source, relational control as a pre-execution regulatory principle, execution eligibility as a stability condition, and non-execution as a valid system outcome. Rather than treating instability as a coordination or optimization problem, the framework demonstrates that stability depends on whether execution is conditionally permitted under relational conditions. Crucially, execution control is not a post-hoc corrective mechanism, but a pre-execution constraint governing execution eligibility and decision finalization. This publication serves as a foundational theoretical paper for the Relationship-Aware AI Research initiative, establishing relational control as a necessary condition for stable multi-entity AI systems.