You have a $50k budget and six weeks to build an SFT da...

The strategy involves a six-week timeline where week one is dedicated to identifying five to ten critical task types and running an AI-generation pilot to measure failure rates. Human annotation resources should be focused on the one or two task types where AI generation consistently fails, such as domain-specific reasoning or regulated content. For the remaining tasks, use distillation from an open-weight 70B model, applying task-appropriate quality filters. The final dataset should consist of roughly 70-90k AI-generated examples and 5-10k human-written ones, with the human examples oversampled by a factor of three in the training batch to mitigate volume imbalance.