Agentic Electronic Design Automation: A Handoff Perspective

Researchers propose a framework for validating handoffs in agentic electronic design automation (EDA) systems, introducing a five-layer communication protocol to ensure LLM-based agents reliably transfer design artifacts across tools and organizational boundaries. The work classifies 82 EDA systems by handoff scope and establishes 'handoff validity' as a key principle for trustworthy AI-assisted chip design workflows.

This academic paper addresses a critical infrastructure gap in AI-assisted chip design by formalizing how autonomous agents should coordinate across fragmented EDA toolchains. Electronic design automation inherently involves multiple handoffs between tools, teams, and stages—each introducing risk when implicit assumptions go unvalidated. As LLM-based agents now directly invoke EDA tools and embed knowledge into executable scripts, the stakes of failed handoffs escalate from workflow delays to potentially flawed silicon designs.

The paper's core contribution is reframing the problem through 'handoff contracts'—explicit agreements about what information must accompany transferred objects, what assumptions downstream consumers can safely make, and how to maintain provenance and evidence chains. By analyzing existing systems across three boundary classes (stage-bound, flow-bound, and organization-bound), the authors expose fragmentation in how different tools and teams currently manage these transitions. This mirrors broader challenges in AI systems integration: agents are powerful within isolated domains but brittle at boundaries.

For the semiconductor industry, this work carries immediate relevance. Chip design cycles are capital-intensive and time-sensitive; automation failures cascade through manufacturing. If agentic tools proliferate without standardized handoff protocols, teams risk subtle design errors that emerge only post-fabrication. The proposed five-layer EDA agent communication protocol (EACP) offers a potential industry standard, similar to how earlier standards accelerated EDA adoption.

The research signals growing maturity in AI-for-engineering discussions, moving beyond raw capability demonstrations toward production-readiness and reliability. Semiconductor companies and EDA vendors should monitor whether EACP gains traction; adoption would reshape how design automation integrates with AI workflows over the next 2-3 years.

• →Agentic EDA systems require formalized handoff contracts to ensure design artifacts meet downstream consumer requirements and maintain provenance across tool boundaries.
• →The paper classifies existing EDA systems into three categories based on handoff scope, revealing fragmentation in how teams currently manage state transfer between tools and stages.
• →A proposed five-layer communication protocol (EACP) aims to standardize agent coordination in chip design workflows, addressing security, IP, and trustworthiness concerns.
• →Failed handoffs in AI-assisted chip design could propagate flawed designs to fabrication, making standardization critical for high-stakes semiconductor development.
• →The research reflects broader maturity in AI-for-engineering, shifting focus from capability demonstration to production reliability and organizational integration.