GEPA: Zero-Config Prompt Self-Evolution via Reflective Mutation & Pareto Optimization
This article details a production-ready GEPA (Genetic-Pareto Reflective Prompt Evolution) system that automates prompt optimization through a data-driven loop of inference, scoring, reflection, and Pareto-frontier selection, replacing manual trial-and-error with a task-agnostic, zero-configuration pipeline that supports classification, scoring, and clustering tasks while preserving explainability.
