Following the Text Gradient at Scale
Summary
Stanford's SAIL blog discusses Feedback Descent, a text-based optimization paradigm that uses rich textual feedback instead of scalar rewards to guide learning. It outlines critique-based and evolutionary methods, introduces a domain-agnostic evaluator-editor loop, and presents results across molecular design, SVG optimization, and prompt optimization.