Dspy Advanced Workflow

It walks you through the seven-step loop: spec out your task, write the typed signature and module, split train and validation data, write a rich metric that returns feedback (not just a score), baseline it, run GEPA optimization with a reflection LM, then export the artifact. The template is opinionated about details that matter: valset should be separate and representative, the metric must return a dspy.Prediction object or aggregation breaks, and you should always baseline before optimizing so you have a claim to make. If you're saying "end to end" or "from scratch," this is the entry point.