Can AI Be Trusted? Synopsys on Agentic AI and Autonomous Engineering

How can engineers trust AI when chip design and simulation demand precision, repeatability, and verifiable results? In this AI Infra Summit interview, Sally Ward-Foxton of EE Times speaks with Thomas Andersen of Synopsys about why the LLM is not the source of engineering truth. Instead, agentic AI serves as an intelligent orchestration layer over trusted, deterministic EDA and simulation engines.

The conversation explores how context-aware, tool-aware agents can plan workflows, invoke the right engineering tools, validate results against design requirements, and adapt when results deviate from constraints. It also examines the importance of token efficiency, including giving models the right context at the right time rather than overwhelming them with unnecessary engineering data.

The interview also looks at what differentiates Synopsys in a crowded agentic AI landscape: domain-specific, long-horizon AgentEngineer solutions and the open, secure Synopsys Autopilot Platform spanning silicon-to-systems workflows. The discussion closes with the practical impact for engineers, from reducing repetitive setup and debug to enabling deeper design exploration, faster productivity, and more connected autonomous engineering workflows.

Watch to learn how Synopsys is advancing engineering-grade AI that is precise, efficient, explainable, and grounded in trusted tools.