A plugin for your agentic framework that optimizes code using the GEPA algorithm (Genetic-Pareto LLM-driven search).

Claude Code for DSPy: Comprehensive CLI to Optimize Your DSPy Code. our AI-Powered DSPy Development Assistant

CLI text optimizer built on GEPA. Uses Agentic Coding CLI's as mutator and observer -- no api keys required

GEPAzilla: open-source GEPA prompt optimizer with datasets, scorers, and telemetry.

Self-evolve Gemini CLI instructions, commands, and skills via the gemini CLI itself — GA + GEPA/DSPy, with hard gates before apply.

A benchmark, alignment pipeline, and LLM-as-a-Judge for evaluating the clinical impact of ASR errors.

A brief experiment applying GEPA (optimize_anything) to automatically compress Python solutions on code.golf.

A reproducible framework that uses DSPy + GEPA-style optimization to auto-tune LLM prompting pipelines for BI workflows (SQL generation, KPI summaries, executive status packs). Optimizes multiple objectives simultaneously—answer quality/faithfulness, token cost, and runtime—using offline eval sets, structured scoring, and Pareto-front selection.

Budge is the experimentation platform for agents.

Acoustic Semantic Instruction Register — LLM-guided hearing-device scene understanding and adaptive DSP parameter generation (DSPy + GEPA)

Summit-Sim uses human-in-the-loop review to generate curriculum-informed, interactive backcountry emergencies for dynamic Wilderness First Responder (WFR) training.

Three-layer agent composition: DSPy signatures (declarative) + PydanticAI (runtime) + pydantic-graph (typed state machine) with GEPA hook via Agent.override()

kinn — a Bayesian diagnostic interview engine. Built with Opus 4.7 hackathon submission, Apr 21–28 2026.

Applied AI & Python Engineer