TypeSafe AI argues good AI evals must be ephemeral, grounded, and specific

TypeSafe AI (@typesafeai) says a good eval snapshots performance at one moment, measures results on the tasks and data a user cares about, and targets desired outcomes rather than proxies.

The post lists these principles without benchmark figures or model names.

A reply from @TimNeumann84165 points to a separate evaluation in which Parallel and co-author @p0 tested eight decision models on audited company training datasets, with Jev ranked first. The reply does not link to that evaluation's results or methods, and TypeSafe AI's post does not refer to it.