Floating-point rounding errors trigger a chaotic "avalanche effect" in early Transformer layers. This arXiv study quantifies how minor numerical perturbations amplify into binary output shifts. The findings explain why identical prompts often yield inconsistent results. Developers must now account for finite precision when building reliable agentic workflows to prevent unpredictable system failures.