Large language models and autonomous agents are increasingly explored for EDA automation, but many existing integrations still rely on script-level or request-level interactions, which makes it difficult to preserve tool state and support iterative optimization in real production-oriented environments. In this work, we present FluxEDA, a unified and stateful infrastructure substrate for agentic EDA. FluxEDA introduces a managed gateway-based execution interface with structured request and response handling. It also maintains persistent backend instances. Together, these features allow upper-layer agents and programmable clients to interact with heterogeneous EDA tools through preserved runtime state, rather than through isolated shell invocations. We evaluate the framework using two representative commercial backend case studies: automated post-route timing ECO and standard-cell sub-library optimization. The results show that FluxEDA can support multi-step analysis and optimization over real tool contexts, including state reuse, rollback, and coordinated iterative execution. These findings suggest that a stateful and governed infrastructure layer is a practical foundation for agent-assisted EDA automation.

翻译：大语言模型和自主智能体越来越多地被探索用于EDA自动化，但许多现有集成仍依赖于脚本级或交互级交互，这使得在真实生产型环境中难以保持工具状态并支持迭代优化。在这项工作中，我们提出了FluxEDA，一个用于智能EDA的统一且有状态的基础设施基底。FluxEDA引入了一种基于托管网关的执行接口，具备结构化的请求与响应处理机制。它还维持了持久化的后端实例。这些特性共同使得上层智能体和可编程客户端能够通过保持的运行状态与异构EDA工具交互，而非通过孤立的Shell调用。我们利用两个具有代表性的商业后端案例研究来评估该框架：自动化布线后时序ECO和标准单元子库优化。结果表明，FluxEDA能够在真实工具上下文中支持多步分析和优化，包括状态复用、回滚和协调的迭代执行。这些发现表明，一个有状态且可管控的基础设施层是智能辅助EDA自动化的实用基础。