Jonathan Frankle, Databricks' chief AI scientist, says evals are the biggest bottleneck to enterprise AI adoption, since models have been good enough for many complex tasks since Claude Sonnet 3.5.
Frankle recommends prototyping with a foundation model and prompt engineering, then moving to custom models once a use case is committed, which he says can cut costs five times or more.