Transformer design refers to the architecture and methodology used in creating transformers, which are deep learning models that leverage self-attention mechanisms to process sequential data more efficiently than traditional RNNs. This design has revolutionized natural language processing and other fields by enabling models to handle longer dependencies and larger datasets with greater parallelization and scalability.