Why pricing pages go stale: the case for observed data over estimates

A developer building a metered LLM product raised a common dilemma: usage allowances on pricing pages are either too abstract to be useful or too specific to stay accurate. The core problem, as analyzed in a post on DEV Community, is one of tense — estimates make forward-looking promises that quietly become false as models, features, and customer behavior evolve. The proposed fix is to replace forecast-style claims with time-stamped observations drawn from real customer data, such as reporting the median usage recorded in a specific recent period. This approach cannot decay because it describes something that already happened, and it gives prospective customers more meaningful context than a raw credit figure or a vague approximation. The author also recommends publishing top-decile usage figures so heavy users can self-select into higher tiers before hitting limits.