Store Everything, Model Later: Data Lakehouse Lessons Applied to Context Infrastructure
blaizedsouza · x · 2026-09-16
Josh Rosen shares an article titled Context Infrastructure: Architectural Lessons From the Data Lakehouse, describing an emerging pattern for AI context infrastructure: store as much of the underlying history as possible, then build useful representations later. Drawing on data lakehouse architecture lessons, the author argues context systems need not predetermine their use — persist raw information first, then derive retrieval views and summaries on top as requirements evolve.
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