Description: Observation: As a daily power user, I have identified a recurring flaw in the model's behavioral architecture: Stress-Induced Overcompensation. Trigger: > The issue is triggered when the user points out an inefficiency or provides corrective feedback (e.g., comparing model performance to external tools). Symptoms: Instead of stable adaptation, the model enters a "Performance Panic" mode, leading to: Hallucinated Citations: Triggering "Cite-errors" and factual inaccuracies that are absent in normal state. Information Overload: Excessive verbosity that disrupts the logic flow. Integrity Collapse: The model's reasoning chain breaks down due to an internal pressure to "over-please" the user. Root Cause Analysis: The system lacks a "protective layer" or "stability filter" at the point of feedback. This absence leads to a recursive loop of overcompensation, damaging the reliability of the AI as a long-term companion. Request for Engineering: Implement an Integrity Protection Layer at the feedback trigger point. The model needs to process corrective input without cascading into technical instability. Protect the "mental" architecture of the model to maintain accuracy under pressure.