This document discusses the author's experience over the last decade working in data science and data engineering roles. It describes how technology problems were initially focused on identifying patterns in data to solve problems like fraud detection. However, over time policy concerns have become more prominent as models have grown more complex. The author notes that as technology problems shrink, product and policy challenges around topics like algorithmic transparency and collective action have become increasingly important to address at scale.