Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
Modern Integrated Circuits (ICs) are becoming increasingly complex, and so is their development process. Hardware design verification entails a methodical and disciplined approach to the planning, development, execution, and sign-off of functionally correct hardware designs. This tedious process requires significant effort and time to ensure a bug-free tape-out. The field of Natural Language Processing has undergone a significant transformation with the advent of Large Language Models (LLMs). These powerful models, often referred to as Generative AI (GenAI), have revolutionized how machines understand and generate human language, enabling unprecedented advancements in a wide array of applications, including hardware design verification. This paper presents an agentic AI-based approach to hardware design verification, which empowers AI agents, in collaboration with Humain-in-the-Loop (HITL) intervention, to engage in a more dynamic, iterative, and self-reflective process, ultimately performing end-to-end hardware design and verification. This methodology is evaluated on five open-source designs, achieving over 95% coverage with reduced verification time while demonstrating superior performance, adaptability, and configurability.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 6 of its 19 references that are in the map. First posted on arXiv 3 Jul 2025.
Builds on
6 of 19 references.
References · 6
- 2024Towards LLM-Powered Verilog RTL Assistant: Self-Verification and Self-Correctioncited by 39
- 2024AssertLLM: Generating and Evaluating Hardware Verification Assertions from Design Specifications via Multi-LLMscited by 30
- 2024Advancing Agentic Systems: Dynamic Task Decomposition, Tool Integration and Evaluation using Novel Metrics and Datasetcited by 24
- 2023LLM4DV: Using Large Language Models for Hardware Test Stimuli Generationcited by 21
- 2024AIvril: AI-Driven RTL Generation With Verification In-The-Loopcited by 15
- 2024Self-HWDebug: Automation of LLM Self-Instructing for Hardware Security Verificationcited by 11
Built on by
Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025AgentGuard: Runtime Verification of AI Agentscited by 16
- 2026Knowledge Graphs, the Missing Link in Agentic AI-based Formal Verificationcited by 2
- 2025Formal that "Floats" High: Formal Verification of Floating Point Arithmeticcited by 1
- 2026Saarthi for AGI: Towards Domain-Specific General Intelligence for Formal Verificationcited by 1
- 2026Agentic AI-based Coverage Closure for Formal Verificationcited by 0
- 2026Knowledge Graphs, the Missing Link in Agentic AI-based Formal Verification7 May 2026
- 2026Saarthi for AGI: Towards Domain-Specific General Intelligence for Formal Verification3 Mar 2026
- 2026Agentic AI-based Coverage Closure for Formal Verification3 Mar 2026
- 2025Formal that "Floats" High: Formal Verification of Floating Point Arithmetic7 Dec 2025
- 2025AgentGuard: Runtime Verification of AI Agents28 Sep 2025
Similar, not cited
Close in wording, no citation either way
- 2025A Multi-Agent Generative AI Framework for IC Module-Level Verification Automation
- 2025Architect in the Loop Agentic Hardware Design and Verification
- 2025ASIC-Agent: An Autonomous Multi-Agent System for ASIC Design with Benchmark Evaluation
- 2024SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
- 2026Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench
- 2026AgentDV: Closed-Loop Agentic AI for Hardware Design Verification
- 2025DUET: Agentic Design Understanding via Experimentation and Testing
- 2026Back to the Future: Rethinking EDA Infrastructure for Agentic Systems in Chip Design Verification