LoRA Foundations for Startup Model Tuning

This opening day of phase-2 establishes parameter-efficient fine-tuning as the core technique for adapting models on limited startup resources. It sets the measurement baseline for all subsequent days by focusing on why full fine-tuning fails at scale and how low-rank methods directly address Maku's tribunal data constraints.