
Medium's feature store became a bottleneck as the data model grew complex. Engineers learned that denormalizing features and separating online from offline storage improved performance. The team also adopted a feature registry to enforce schema consistency and reduce debugging time across ML pipelines.
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AI's Real Bottleneck Is Infrastructure, Not Models
Summary by ByteBrief