Automatic Prompt Optimization(APO)

Treats the prompts and instructions inside an agent pipeline as learnable parameters that are optimized programmatically against a metric and a labeled dataset, instead of being hand tuned. Optimizers bootstrap few-shot demonstrations and search over instruction wordings, and reflective methods mutate prompts by reading execution traces of past failures.