LLMs do NOT think linearly—they generate in parallel

Internally, LLMs work by: • embedding the entire prompt into high-dimensional vector space • performing massive parallel matrix operations • updating probabilities across thousands of dimensions simultaneously • selecting tokens based on a global pattern, not a linear chain

The output is linear only because language is linear.

The thinking behind the scenes is massively parallel inference.