RFIC design, rebuilt around AI

Digital chip design has run on algorithms for forty years: place and route, timing closure and verification are solved problems. RF design never got there, because RF performance depends on physical effects that interact continuously rather than digitally: bias, stability, noise figure, impedance matching, layout parasitics, process corners and EM coupling all move together, and a small error in any one of them shows up as bad silicon.

No textbook formula captures that interaction. Engineers learn to navigate it the way any craft is learned: by designing hundreds of circuits, watching what comes back from the fab, and building an intuition that cannot be written down as a decision tree. That is why RF engineering earned its reputation as black magic, and why it resisted the kind of automation that transformed digital design decades ago.

We are building toward what we call the artificial RF design engineer: an AI that develops expert level solutions for any RF specification, collaborates with engineers on novel architectures and trade off decisions as a true co-pilot, and scales from a single component to a complete RF system. It already generates and optimizes full circuits end to end, and lets engineers compare candidates and choose their own trade offs today.

What is coming is a platform that keeps expanding: reaching any circuit type beyond amplifiers, growing with large scale RF models and faster AI solvers, and open to engineers bringing their own architectural knowledge directly into it, always on their own terms. This is not a distant roadmap. The foundation is built, the stack is running, and the direction is clear: RF engineering gets its own artificial design engineer, the way digital design got its algorithms, only faster, and built for the engineers who use it.