A structured, systems-level exploration of reflection and recursive development in intelligent systems.

This Technical Perspective from Chapter 22 analyses how sustaining intention and growth in AI requires memory mechanisms, calibration thresholds, and recursive self-assessment.

Drawing parallels with biological cognition and metacognitive learning, it explains how loops may decay or evolve depending on system design.

Recorded in a measured technical tone (Audacity, Arty-style), this voice track supports deeper engagement with the conceptual architecture of spiral evolution.

New tracks tagged #memory systems