Shrewd is a library that distills LLM judgments into small, fast local text classifiers for fixed tasks. The author shares findings from building the pipeline, including that prompt optimization gains often don't persist on held-out data, and that selecting informative training examples outperforms cheaper labels or escalating uncertain cases.