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Git packfiles use delta compression, storing only the diff when a 10MB file changes by one line, while the objects table stores each version in full. A file modified 100 times takes about 1GB in Postgres versus maybe 50MB in a packfile. Postgres does TOAST and compress large values, but that’s compressing individual objects in isolation, not delta-compressing across versions the way packfiles do, so the storage overhead is real. A delta-compression layer that periodically repacks objects within Postgres, or offloads large blobs to S3 the way LFS does, is a natural next step. For most repositories it still won’t matter since the median repo is small and disk is cheap, and GitHub’s Spokes system made a similar trade-off years ago, storing three full uncompressed copies of every repository across data centres because redundancy and operational simplicity beat storage efficiency even at hundreds of exabytes.
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总结与展望未来，智能体将会是我们在各行各业、各种场景应用人工智能的主要载体。可以预见，随着模型能力和智能体工程的进步，企业数据治理和组织适配的提升，智能体会逐步成为每家企业极有竞争力的数字员工，和我们人类员工竞争与协作。