这篇论文分析了LLM在EDA领域的三种角色定位，揭示了当前系统的局限性，提出了向协调器转变的必要性。
该研究论文探讨了大型语言模型在电子设计自动化领域的作用演变。作者提出了三种层次角色：生成器、智能体和协调器。当前系统面临语法陷阱，模型被训练生成看似合理的代码而非物理正确的硬件。研究指出需要向标准化、物理感知的协调器转变，以实现更可靠和易用的硬件设计。
LLMs in Digital EDA: A perspective on shifting roles from Generation to Orchestration
Electronic design automation (EDA) has advanced engineering productivity through successive generations of tooling that progressively automate synthesis, optimisation, and verification. Large language models (LLMs) extend this trajectory by enabling direct translation from design intent to hardware implementations. In most of the EDA literature, LLM-based solutions are typically assisting siloed design stages or tasks, however this obscured the drivers by which capability emerges and systems scale. In this Perspective, we instead define three hierarchical roles that reveal how capability accumulates: a Generator that produces design artifacts in a single pass, an Agent that refines outputs through iterative tool feedback, and an Orchestrator that coordinates decisions across EDA-stages. Across published systems, this reveals a syntax trap in which models are trained to produce plausible code rather than physically correct hardware, compounded by fragmented tools and loss of design context that obscure how decisions affect later stages. Comparisons across the three roles show that current approaches struggle to scale to industrial designs, motivating a shift towards a standardised, physics-aware orchestrator that connects tools and agents across the EDA flow for more reliable and accessible hardware design.