Researchers propose Graph-Regularized Agentic Context Evolution (GRACE) to improve the reliability of long-horizon context evolution for deployed LLM agents. GRACE maintains the agentic context as a typed semantic graph and validates updates within local neighborhoods, achieving better results than a baseline approach in a controlled experiment.