As post-training moves beyond one-off projects, SME trainers face a hybrid future: enterprises develop internal capability and partner externally for scale, coverage, and consistency.
As RLaaS and RL environments move into enterprises, domain experts who can operationalize reward semantics, evaluator QA, and trajectory-level evaluation become the constraint.
For a long time, “AI training” was easy to explain. You gathered a big dataset, hired enough people to label it, ran quality checks, and shipped the model. That workflow still exists, but it’s becoming less true in the places where performance actually matters.
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