This article discusses Recursive Language Models (RLMs) as a solution to the problem of context rot in large language models. RLMs utilize a REPL environment to manage long contexts efficiently, enabling models to maintain performance even with extensive input data. The author highlights their potential for agent design and optimization while acknowledging current limitations.