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From AI-Assisted EDA to AI-Mediated Engineering
Reflections on DAC 2026, where agentic methods made up about 28% of the agenda and AI submissions had risen from under 300 in 2023 to about 700. Sets out the two technical routes, replacing the tool engines or wrapping them, and argues for evidence-grounded loops in which AI proposes and physics, formal methods or simulation decides.
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Harnessing AI for SoC Verification: Disruptive or Collaborative?
Panel on whether AI in SoC verification disrupts current flows or works alongside them.
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AI in EDA Is Real, It's Now, and It's on Show at DAC 2026
Frank Schirrmeister's preview of DAC 2026, built around two ideas from my work. Davidmann's Dilemma: "every camp acting rationally guarantees the collectively wrong outcome". Davidmann's Test: "Does it change what you can verify, or just how fast you run what you already verify?"
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The next EDA wave: Lessons from DATE 2026
A review of DATE 2026 in Verona. AI now appears as a workload, a design tool, a research method and a security risk, and the move from single prompts to multi-agent, tool-grounded flows makes verification and security first-class constraints. Closes with the case for European capability in AI+EDA, built on its universities, its RISC-V community and its safety-critical industries.
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Creating Agentic EDA Methodologies
Quoted on agentic EDA flows across many tools, vendors and data formats, and on companies with very large resources building their own AI solutions in-house.
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The Magic of Agentic AI Will Come From a Holistic Approach to Chip Design
Interview on agentic AI in chip design. Most agentic tools today optimise existing flows; larger gains come from treating design, synthesis, verification and layout as one system, which some large technology companies already do in-house. New EDA start-ups aiming at step-function improvements need investors prepared to fund them.
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What is the EDA problem worth solving with AI?
Most AI work in EDA speeds up what engineers already do. This article looks at the positions of the large EDA vendors, the agentic start-ups and the in-house teams at large chip companies, and proposes foundation models specialised with formal and domain structure, open APIs and serious collaboration between industry and universities.