Counting duplicates in a spreadsheet should be straightforward. The fact that a user has to manually tally 11 duplicates, 2 triplicates, and 3 quadruple-or-more entries across a modest dataset tells you everything about the gap between what spreadsheets promise and what they deliver. This is not a critique of the user, it is a critique of the tool.
The user's data is clean and structured: sixteen rows of numbers, each row holding six values. The results are known. Yet the question remains which formula to use. Traditional spreadsheet functions like COUNTIF can technically handle this, but they require nested logic, careful range locking, and a separate column for each duplication tier. For a non-trivial count like "how many numbers appear exactly three times," the formula becomes a fragile tower of conditions. One misplaced dollar sign and the counts shift. This is not empowering. It is a tax on productivity that we have accepted for decades.
What this user needs is not a better formula, it is a better relationship with their data. An AI-native spreadsheet should let you ask, "Show me the frequency distribution of all numbers across these rows" and receive the answer instantly, without constructing a single equation. The machine should do the counting; the human should do the thinking. The user already did the hard part: they knew what they wanted to know. The tool failed to meet them halfway.
So here is our plain opinion: if your spreadsheet requires you to manually verify results you already know, it is not serving you. The future of data work is not about memorizing COUNTIF syntax or debugging array formulas. It is about asking natural questions and getting precise answers. This user's manual tally is a sign of diligence, but it should also be a signal that the technology has room to grow. The next step is to explore tools that treat your data as a conversation, not a calculation puzzle.