RSIAgent is a training‑free multi‑agent framework that enables autonomous agents to recursively improve themselves in unfamiliar environments by building and retaining environment‑specific memory. It employs curriculum, actor, and verifier agents to explore, test actions, and capture reusable causal relationships between actions and outcomes. This approach allows continual adaptation without retraining pretrained models.