AI RESEARCH

Understanding the Challenges in Iterative Generative Optimization with LLMs

arXiv CS.LG

ArXi:2603.23994v1 Announce Type: new Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using execution feedback. It is a promising approach to building self-improving agents, yet in practice remains brittle: despite active research, only 9% of surveyed agents used any automated optimization.