Plan an embedding model migration with versioning, side-by-side evaluation, and rollback.
Migration risk A model upgrade is available, but the current index contains millions of vectors from the old model. If query and document vectors come from incompatible spaces, nearest-neighbor scores become misleading. PDCA migration loop Plan -> Do -> Check -> Act for embeddings An embedding migration should prove that the new vector space improves retrieval without breaking latency, cost, or access controls. Shortcut Change the query model and watch production. A model upgrade that changes search quality by evidence, not hope. Model version belongs in retrieval data because it defines the coordinate space. 01 Plan 02 Do 03 Check…
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