A new AI Training Manager system uses bounded LLM-based metacognitive monitoring-and-control to optimize machine learning training. It observes telemetry, assesses the training regime, and selects adaptive interventions to prevent overfitting and improve performance. This approach shows promise for practical metacognitive control over ongoing learning processes.