A practical walkthrough of how the Transformer architecture evolved from encoder-decoder to decoder-only models, why attention’s quadratic scaling became a hard wall, and how Mamba’s state space machines are being absorbed into hybrid architectures that dominate production today.

A practical deep-dive into how the Transformer’s encoder and decoder stacks work, covering residual connections, positional encoding, masked self-attention, and cross-attention with code examples throughout.