Structural templates: the matching layer vectors can't see
Embeddings blur exactly where caches need precision — numbers, dates, entities. Template abstraction catches what cosine similarity structurally cannot.
Embeddings have a known blind spot: they compress meaning into geometry, and small tokens with huge semantic weight — negations, identifiers, quantities — barely bend the vector. 'Invoice #4412' and 'invoice #9981' embed nearly identically, which is correct for similarity and catastrophic for a cache that might serve one customer's invoice status to another.
Crowkis's template engine attacks the problem from the structural side: numbers, dates, IDs, and entities are lifted out of the query into typed slots, and the remaining skeleton — 'status of invoice <ID>' — is hashed. Two queries match structurally when their skeletons agree; their slots are then compared explicitly, where <ID>=4412 versus 9981 is an unmistakable mismatch rather than a rounding error in cosine space.
Reuse only when meaning, structure, confidence, and trust all agree.
The dual requirement is the safety story: a hit needs the vector to say 'same meaning' and the template to say 'same structure, compatible slots.' Each side covers the other's blindness — vectors catch paraphrase that templates can't, templates catch precision that vectors can't. Single-signal caches choose one blindness; we declined.
The bottom line
Templates also multiply hit rates on parametric traffic: one cached skeleton serves infinite slot variations of commands, lookups, and form-letter queries. The layer that protects you is the same layer that pays you.