The article explores how language models, specifically Claude 3.5 Haiku, learn to handle line-breaking tasks in fixed-width text by developing perceptual mechanisms akin to biological models like "place cells." It examines dual interpretations of learned position representations and highlights the challenges language models face in predicting line breaks based on character counts and formatting constraints. The work emphasizes the unique ways these models adapt to text-based environments despite their limited sensory inputs.