Attention Algebra is a prototype that translates natural language into algebraic expressions, maps them to mathematical dynamics, and visualizes the result as a spectrogram. It treats language as a lossy projection of high-dimensional states, proposing that raw attention patterns grouped into functions serve as the 'DNA' of text, enabling efficient reasoning chains by reducing token usage from 20k to 4k.