tag: agentic AI

Preparing For AI-Driven Chip Design And Verification
By Ed Sperling - 27 Jul, 2026 - Comments: 0

Key Takeaways: Agentic AI will fundamentally change how engineers approach design and verification, and it will require them to adapt or be left behind. AI is a black box, so ensuring reliability will require external observability through sandboxing, along with other safeguards in case something does go wrong. The concentration of profitability in a few companies will shift as agent... » read more

Why Chip Engineers Should Care About AI-Created Behavioral Models
By Sidharth Kannan - 23 Jul, 2026 - Comments: 0

You probably know this bottleneck too well: full transistor-level or physical simulations—whether analog circuit, electromagnetic, or thermal—can take weeks or even months. For complex designs, simulating every internal transistor in every block quickly becomes impractical. This is why creating accurate behavioral models is so important. A good behavioral model captures a block's input-o... » read more

The Impact Of AI Automation On Chip Design
By Brian Bailey - 23 Jul, 2026 - Comments: 0

Key Takeaways: Tools are currently built with a defined notion of how they will be used. For agentic solutions they will be transformed into collections of callable engines. Agents may be built by EDA companies for design houses or larger design houses may build their own, potentially transforming the EDA business model. The role of engineers will change, but exactly how is not certa... » read more

AI In Chip Design: Lots Of Promise, Plenty Of Unanswered Questions
By Ed Sperling - 15 Jul, 2026 - Comments: 0

Key Takeaways: AI opens the door to exploring a much larger solution space, similar to what high-level synthesis did years ago, but questions persist about the impact of increasing reliance on what is essentially a black-box chip design. There is no consistent answer to how successful AI will be, where it will succeed or fail, or how it will apply to different markets and EDA customers.... » read more

Innovation First, AI Second: Lessons From SSN And The Future Of Test
By Marc Hutner - 13 Jul, 2026 - Comments: 0

By Marc Hutner and Ron Press Artificial Intelligence is rapidly becoming pervasive in society and across semiconductor development processes. We have to be careful not to apply AI to solve optimizations and challenges of existing methods but pair with engineering innovation for evolutionary results. One example is the application of scan test data in multi-core designs. AI can optimize the d... » read more

The Architecture Decisions Behind A Production-Ready EDA AI Agent
By Emma-Jane Crozier - 09 Jul, 2026 - Comments: 0

The conversation about agentic AI in semiconductor and PCB design tends to focus on capability: what the agent can do, how much time it saves, and which parts of the workflow it can automate. That is a reasonable place to start, but that is not where the hard engineering happens. Organizations are now asking whether AI agents can take on meaningful portions of the workflow, not as assistants th... » read more

From Host Node To Heterogeneous Rack: Rethinking The AI CPU
By Satadal Bhattacharjee - 09 Jul, 2026 - Comments: 0

AI infrastructure is entering a crucial new phase. The first phase of generative AI infrastructure was defined by accelerator scale: how many GPUs, NPUs or custom AI accelerators could be deployed, powered, cooled and connected. That phase is not over, but it is no longer sufficient. The next phase is about rack-scale system composition: heterogeneous AI racks where different compute resourc... » read more

A Self-Evolving Agent Framework That Treats Hardware Design as Repository-Level Code Evolution (Nvidia Research)
By Technical Paper Link - 30 Jun, 2026 - Comments: 0

A new technical paper, Agentic Hardware Design as Repository-Level Code Evolution, was published by researchers at Nvidia Research. Abstract "We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled into a project pack containing domain knowledge, an executable evaluator, an acceptance predicate, and... » read more

Verification Methodologies Struggle To Keep Up With AI
By Brian Bailey - 25 Jun, 2026 - Comments: 0

Key Takeaways:  The rapid development of AI has resulted in new capabilities being provided to verification teams, beyond their ability to rationally insert them into accepted methodologies. There is a lot of uncertainty about who will benefit the most from this technology. Is AI a junior engineer replacement or an enhancer? The biggest benefits will come when AI helps engineers und... » read more

Executive Outlook: Agentic AI’s Impact On Chip Design
By Ed Sperling - 25 Jun, 2026 - Comments: 1

Key Takeaways: Agentic AI has the potential to make engineers more productive, speed time to market, and automate some of the drudge work. The big challenge for design and verification engineers is where and whether they trust AI to get everything right, because there is no margin for error in semiconductors. Having humans in the loop will likely be the rule rather than the exception... » read more

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