this is pure f*cking treasure A Stanford AI research group has found a way to use JEV to make your LLM run 24/7 at a lower cost in x444 the LLM only does what needs words. everything else is a typed decision: > worth reading? Jev answers yes or no before a single token is spent > which desk? papers, repos or market, one Choice > rerank: embeddings pull 20 sources, Jev keeps the 5 that matter > claim holds? every claim checked against its source, the weak ones dropped > new or known? duplicate, related, revises or contradicts, checked against the vault the LLM writes one note, 5 to 12 lines, one claim > judge: confident verdicts pass, unsure ones go up to a frontier model > matters to you? only the top scores make the morning brief the judge rule comes straight from Carnegie Mellon's JEV-as-a-Judge paper: escalate only the unsure 34%, keep 99.6% of the accuracy at 47% of the fee and the fees are the whole point > Jev: $0.044 per 1,000 judgments > GPT-6: $12.182 for the same 1,000 a whole day of decisions on a frontier model costs dollars. the same day on Jev costs cents you stop reading 300 sources. you read one brief