GEPA

Headlines · 1

1. 4h
   Gear open-source framework targets recursive AI self-improvement

   Gear developers introduced an open-source, meta-learning-inspired framework in which a task agent produces execution traces and a meta-agent uses those traces and evaluation feedback to improve prompts, tools, workflows, and context management. The framework separates search decisions from execution and evaluation and includes a working GEPA variant with shared failure diagnosis and staged evaluation. Its stated goal is to make methods such as GEPA, RRSI, and Harness² easier to implement and compare. Developers reported higher task pass rates with Gear-optimized configurations using GPT 5.6 Luna at medium reasoning effort, but supplied no independent measurements.

   r/MachineLearning · 🔥 5

Experience and discussion from the community

Share my GEPA experienceAsk about GEPA