GEPA (Genetic-Pareto) is a framework for optimizing any system with textual parameters against evaluation metrics. It uses LLM-based reflection and Pareto-efficient evolutionary search to iteratively improve prompts, code, agent architectures, and configurations. The system applies genetic algorithms with LLM-guided mutation and selection to discover optimal parameter combinations across multiple objectives.