Or prompt(n) time, where n = the known minimum # of prompts required to solve a given class of problems. From there we can define various classes of problems:

Or prompt(n) time, where n = the known minimum # of prompts required to solve a given class of problems. From there we can define various classes of problems: 1) those with an absolute floor minimum # of required prompts 2) those with a known ceiling Etc. This should be combined with traditional Big-O notation to provide a more specific classification, e.g. a constant-time complexity task with a known ceiling of two prompts would be prompt(2)-O(1) A problem known to, in some specific cases but not all, be solvable with some minimum number of prompts with no ceiling known might be Prompt(n(np)) where n = minimum prompts known to solve at least some problems in that class. Classifications would be applied to specific systems but the best performing system would set the general classification for a problem. So the general classification for a problem might be prompt(1(5)) to denote a min 1 max 5 prompts required based on the best performance seen to date, a specific system might only rate a prompt(3(np)) classification. I’m overthink this but I think I like it.