For decades, analog design has stubbornly resisted automation, even as significant parts of digital design flows have embraced it. The reasons for this resistance were embedded in the fact that analog designs were small and “easy'” for an expert to comprehend. Despite the efforts of the brightest minds, using the best mathematical techniques of the time, analog EDA tools have struggled in competition with the expert. Has ML changed anything? This talk is based on recent experience with developing ALIGN, an open-source analog layout automation flow that has been applied to a wide range of design types and technology nodes. The talk overviews the lessons learned – the advantages, as well as the perils and pitfalls – of applying ML to analog design to enhance designer productivity.