Learning and self-improvement
Feedback loops that stay evidence-backed — regressions block promotion.
Trials are hashed, redacted, and integrity-chained before entering any improvement pipeline.
Evaluation harnesses and multi-metric scorers provide multi-metric gates, not a single loss.
Online feedback tracks accept / reject signals with safeguards and deployment cadence awareness.
Optional advanced training paths exist; offline-first defaults remain the norm.