How Tokenization Quietly Taxes Every AI Product You Ship
Tokenization is the subword-splitting step every large language model runs before it ever reasons about your prompt, and it isn't neutral. The same byte-pair-encoding process that makes English cheap to process can cost 50% to over 12x more tokens for other languages, and it explains why models stumble on letter-counting and arithmetic. As AI products expand into global markets, tokenizer behavior is turning into a hidden line item in unit economics and a real security surface, not just an engineering footnote. For PMs, the fix starts with actually measuring token counts across the languages and data types your product claims to support.