Training loss is a weak proxy for specialist correctness. Domain systems need task-level evaluation, failure taxonomies and operational checks before they are treated as dependable.
Read articleNot every domain problem needs continued pretraining. A practical framework for choosing between data exposure, instruction tuning and lighter adaptation methods.
Read articleRetries are not a recovery strategy. Reliable agents need state, checkpoints, tool contracts and explicit paths for partial failure.
Read articleNext step
Bring the domain, constraints and current system. We will help determine what is feasible, what should be measured and what is worth building.
Initial conversations are exploratory and confidential.