Cost-Efficient Agent Scaling via Knowledge Distillation on Amazon SageMaker
Amazon has published a workflow for using Sequence-Level Knowledge Distillation (SeqKD) to fine-tune smaller models on trajectories generated by frontier models. By using a 'teacher' model to generate successful tool-use trajectories and filtering them with a programmatic scorer, teams can train compact 'student' models that perform complex reasoning at a fraction of the cost.