Quality Over Scale: Training the 50M-Parameter Scout Model

Training small language models (SLMs) reveals that data quality is far more critical than raw scale for achieving coherent outputs. By leveraging Claude Code for automated qualitative checks, developers can move beyond simple loss metrics to truly understand a model's cognitive progress.