de. They are difficult to train since experience and intuition are the traits that characterize them. And they have difficulties in explaining what is the process they use to reach satisfactory results. Tools used for design (sim- ulation) are mainly replacing the test benches of an experimental lab. However, the growing complexity of the integrated systems being designed today together with the increasing fragility of analog components brought about by shrinking geometries and reduced power consumption is posing severe challenges to traditional analog designers to produce satisfactory results in a short time. At the same time, the need for experi- enced analog designers has increased constantly since almost all designs, because of integration, do contain analog components. This situation has created a strong interest in developing design methodologies and supporting tools that are based on rigorous, mathematically literate, approaches. Doing SO will make it possible to leverage the expertise of seasoned analog designers and to train new generations faster and better. In the past, several attempts have been made in academia and industry to create these methodologies and to extend the set of tools available. They have had questionable acceptance in the analog design community. However, recently, a flurry of start-ups and increased investment by EDA companies in novel tools signal a significant change in market attention to the analog domain. I personally believe that to substantially im- prove quality and design time, tools are simply insufficient. A design methodology based on a hierarchy of abstraction layers, successive refinement between two adja- cent layers, and extensive verification at every layer is necessary. To do so, we need to build theories and models that have strong mathematical foundations. The analog design technology community is as strong as it has ever been. Mathematically astute researchers are advancing the state of the art of simulation technology at a pace as fast as I have ever seen in my