Exciting to see how fast agentic AI chip design is making its way into academia. This semester, ChipAgents’ multi-agent root cause analysis system has been incorporated into coursework at Harvard University bringing real-world AI-driven chip design insights directly into the classroom. Today, our team also had the opportunity to give a guest lecture on superhuman chip design at Stanford University EE sharing an industry perspective on multi-agent AI for chip design and verification. One analogy that resonated: the relationship between foundation models and agentic AI is like an F1 team. McLaren can beat Mercedes in 2024 and 2025 while still using Mercedes engines. The LLM is the engine, but building a winning F1 car is far more complex. And even then, teaching someone to drive that car at the highest level is another challenge entirely. That’s where agentic systems come in. The intersection of academia and industry is where real breakthroughs happen, and it’s energizing to engage with the next generation of engineers on these topics. Thanks Stanford!