Medical terminology specifically, not healthcare broadly, because a narrower target produces a cleaner training set.

The first pass was noisy enough that an early adapter did worse than the base on some held-out prompts. Curation ran longer than expected.

Once the data was clean, training took hours, not the days a full fine-tune would have needed.

Fixed the evaluation set before training finished, so there was an honest bar to clear rather than cherry-picked examples.

Made so a non-technical stakeholder could see the difference themselves instead of taking a score on faith.

Deliberately ran unrelated prompts so the limits of the narrow gain were known upfront, not discovered by a confused user.