AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent

arXiv:2604.06296v2 Announce Type: replace-cross Abstract: AI agents are increasingly deployed in real-world applications, including systems such as Manus, OpenClaw, and coding agents. Existing research has primarily focused on server-side efficiency, proposing methods such as caching, speculative execution, traffic scheduling, and load balancing to reduce the cost of serving agentic workloads. However, as users increasingly construct agents by composing local tools, remote APIs, and diverse mode