OneDayAgent: A New Harness for Long-Horizon Autonomous Agents

A recent research article presents OneDayAgent, a framework designed to oversee autonomous agents engaged in complex, open-ended tasks. This paper, accessible on arXiv (2608.05013), tackles the difficulties agents face when managing daily requests that encompass work, study, and personal life, which are characterized by long durations, multiple environments, and various modalities. While earlier studies have focused on specific failure modes such as goal drift and context overflow, OneDayAgent seeks to address these issues collectively across various backends. It breaks down tasks into manageable subtasks, preserves execution memory under contextual stress, and ensures the accuracy of final outputs. Tested on the AgentIF-OneDay benchmark with 104 tasks, OneDayAgent sets a new benchmark score using the GLM-5.2 backend. Authored by a team of researchers, this paper is submitted for publication and represents a significant advancement in AI agents, offering a cohesive solution to prevalent challenges in long-term task management, thereby enhancing the reliability and efficiency of autonomous systems in practical scenarios.