We keep hitting tasks where prompt tricks plateau but full fine-tuning feels heavy. LoRA/PEFT narrowed the gap, but the ops burden (data pipelines, eval regressions) is real. How do you decide when a problem deserves fine-tuning versus better prompting or retrieval? Any rules of thumb that survived contact with production?