Agentic Electronic Design Automation: A Handoff Perspective
A survey of 115 LLM-based agent systems across the EDA flow, organized around producer-to-consumer handoffs — the objects they transfer, the acceptance evidence each downstream stage requires, and the missing shared infrastructure for trustworthy agentic EDA.
Abstract
Electronic design automation (EDA) is multi-stage and handoff-heavy, relying on transfers among humans, design artifacts, and multiple tools. LLM-based agents now participate in these transfers, yet the resulting research landscape is highly fragmented and lacks a unified perspective.
This survey adopts the primary input–output pair as its organizing lens: for each agent system, we analyze its primary, supporting, and intermediate handoff objects and classify it according to the provenance of its primary input and the consumer boundary of its primary output. Intra-stage systems operate on objects within a single EDA stage, inter-stage systems transform EDA-native artifacts into forms usable by downstream stages, and extra-stage systems translate human intent into EDA artifacts.
Based on this taxonomy, we survey 115 representative systems and examine them along multiple dimensions, including research trends, benchmarks, and model mechanisms. Finally, we outline an agentic EDA protocol roadmap and discuss open problems for future research.
Overview
Core distinction. Agentic EDA systems differ in where their primary input originates and where their primary output is consumed. Two properties determine the class:
- Input provenance — is the primary input a machine-readable EDA-domain object, or human-originated intent and knowledge?
- Consumer boundary — is the primary output checked and reused within the same stage, or accepted across a representation boundary by a downstream stage?
The complete set of handoff objects is written as ℛ = (Ip, Op, Is, Os, Am; M): primary input/output, supporting inputs/outputs, intermediate artifacts, and metadata.
Taxonomy
The three-class taxonomy follows directly from the primary input–output pair. Supporting objects, intermediate artifacts, metadata, model architecture, mechanisms, and benchmarks remain descriptive dimensions and do not determine the primary class.
Intra-stage36 systems
- Consumes a machine-readable EDA-domain object (design artifact, EDA-tool code, or measurements).
- Output is checked and reused within the same stage — compilation, simulation, equivalence, PPA, lint/DRC, or coverage.
- e.g., RTLFixer, ADO-LLM, MappingEvolve, ModelGen.
Inter-stage16 systems
- Consumes an EDA-native representation and produces a different design-stage representation.
- Acceptance relies on cross-tool execution, downstream validation, QoR, or checkpoint coherence across the boundary.
- e.g., HLSPilot, HyperPlace, PCBAgent, ChatEDA.
Extra-stage63 systems
- Begins from human-originated text, queries, or documents and produces a machine-consumable EDA artifact.
- Acceptance depends on specification completeness, provenance, and attribution to inspectable sources.
- e.g., VerilogCoder, AssertLLM, ChatLS.
Research trends
Agentic EDA research is expanding rapidly and unevenly. The corpus grows from 1 system in 2023 to 25 in 2024, 46 in 2025, and 43 by the August 31, 2026 cutoff — the 89 systems from 2025–2026 account for 77.4% of the corpus. DAC contributes 38 systems alone.
Quick start: representative systems
These are not the only important systems in the survey. They are a first reading path across the three classes — one canonical example of each primary input–output setting — before diving into the full library.
A canonical compile–repair loop: an LLM fixes RTL syntax errors and re-iterates against Icarus Verilog / Quartus feedback.
Code →Analog sizing via Bayesian optimization with in-context learning, gated by simulation and fitting error within the same stage.
LLM-driven evolution of technology-mapping tool code, with each edit accepted by a stage-local optimizer.
Code →Autonomous orchestration from RTL to implemented layout, coordinating netlist synthesis, placement, and routing scripts.
Code →LLM-based high-level synthesis that crosses the software-to-hardware representation boundary.
Agent-based high-density PCB placement, producing a layout that downstream routing tools must accept.
Autonomous Verilog coding agents with graph-based planning and AST-based waveform tracing from natural-language specs.
Code →Generates hardware verification assertions from design specifications — human intent translated into machine-checkable collateral.
Multimodal retrieval-augmented logic-synthesis script customization, grounded in tool manuals.
Curated system library
All 115 surveyed systems, grouped by handoff class and primary input–output pair. The Primary I/O column reports Ip → Op. Filter by class, recency, or code availability, or search by name, title, venue, or task family.
How to read this survey
Agentic EDA Protocol Roadmap
General-purpose agent protocols separate discovery, messaging, tool access, workflow description, and identity — but they do not record the EDA-specific object roles, acceptance evidence, configuration fingerprints, dependencies, and PDK/IP policies the surveyed workflows require. The roadmap organizes these missing semantics into five layers, each pairing a recurring coordination gap with a required capability and a validation milestone.
A versioned capability manifest and registry that encodes process node, PDK, library, and tool assumptions, rejecting incompatible agents with explainable verdicts.
A shared, versioned handoff message that distinguishes primary and supporting objects from candidates and workflow state, and identifies the evidence used to accept the primary output.
A typed operation descriptor with backend-specific adapters returning checker results and QoR with comparable units, artifact references, and error categories across tool versions.
A workflow representation in which each edge identifies its producer, consumer, objects, accepted configuration, and dependencies, with recorded evidence gating every transition.
Authorization, disclosure, retention, and audit semantics that determine whether a handoff is authorized, appropriately disclosed, protected, and admissible for organizational reuse.
Community & feedback
Citation
Please cite this survey as follows.
@article{liu2026agenticeda,
title={Agentic Electronic Design Automation: A Handoff Perspective},
author={Liu, Jiawei and Han, Peiyi and Lu, Yuntao and Zheng, Su and Yan, Fengyu and Yu, Bei},
year={2026},
eprint={2606.19795},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2606.19795},
}