The Saturation Trap and the Subjectivity of Intervention Timing: Why Affect-Based Triggers and LLM Judges Fail to Time Interventions on Autonomous Agents

This paper investigates the problem of timing interventions on autonomous AI agents, using a continuous 18-dimensional affective-dynamics engine as a diagnostic probe. It identifies a 'State Saturation Trap' where agents show no recovery signal under sustained difficulty, and a capability-and-context floor for LLM judges, making intervention timing a complex challenge.