This paper presents the DNA Family, a new framework for boosting the effectiveness of weight-sharing Neural Architecture Search (NAS) by dividing large search spaces into smaller blocks and applying block-wise supervisions. The approach demonstrates high performance on benchmarks such as ImageNet, surpassing previous NAS techniques in accuracy and efficiency.