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Synopsys Brings Agentic Engineering Into Focus as AI-Driven Design Tests Productivity Limits
Apr. 02, 2026 –
Faster AI-driven design is exposing a productivity paradox as efficiency gains increasingly depend on higher compute
By Yashasvini Razdan , EE Times
A recent rise in attention around Synopsys, following an activist stake by Elliott Investment Management, is bringing new focus on how AI is evolving from a technical upgrade in engineering workflows into a driver of growth.
From chip design to system-level simulation, AI permeates every layer, promising to compress development cycles from years to months. Faster design cycles and higher iteration counts are no longer just engineering benchmarks; they are increasingly being viewed as indicators of future growth. However, as companies scale compute spending and experiment with generative design and AI-driven simulation, where are the tangible productivity gains emerging, and more importantly, is there a gap between demonstrated capability and repeatable, real-world productivity gains?
EE Times spoke to Prith Banerjee, senior VP of Innovation and a member of the executive leadership team at Synopsys, as the company expands its chip design tools into system-level simulation following its $35 billion acquisition of simulation behemoth Ansys. Banerjee, who previously served as the CTO of Ansys, said Synopsys is betting that AI-driven simulation, generative design, and what it calls “agentic engineering” can significantly reduce design cycles and improve product quality.
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