Use case
Jev for RAG: filter and route, do not write the answer
RAG still needs a generator. Jev’s hypothesized job is scoring or routing retrieved context before the LLM spends tokens.
Where a model belongs in a stack — the seat, not the implementation. How-tos stay off this site.
RAG still needs a generator. Jev’s hypothesized job is scoring or routing retrieved context before the LLM spends tokens.
Agents still need a writer and a tool-caller. Jev’s claimed seat is the cheap, typed checkpoint between steps.
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