A model reads a long Hausa news report, and the question at the end needs a name from the first line. Compare full attention, a sliding window and a local-plus-strided pattern, and see how far each can reach, then fix the weight wasted on the first token with differential attention. Then use a window everywhere with too few layers, full attention on a huge context, or plain softmax. This lesson needs JavaScript.