AI RESEARCH
EvoClaw: Evaluating AI Agents on Continuous Software Evolution
arXiv CS.AI
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ArXi:2603.13428v1 Announce Type: cross With AI agents increasingly deployed as long-running systems, it becomes essential to autonomously construct and continuously evolve customized software to enable interaction within dynamic environments. Yet, existing benchmarks evaluate agents on isolated, one-off coding tasks, neglecting the temporal dependencies and technical debt inherent in real-world software evolution. To bridge this gap, we