There is a simple, frustrating truth at the heart of this COUNTIFS problem: you are not crazy, but the spreadsheet is reading your data differently than you expect. The user who posted this has done everything right, converting lowercase to uppercase, trying both `TRUE` and `"TRUE"` as criteria, yet the function stubbornly returns zero. What they are overlooking is that their column K likely contains text strings that look like `TRUE` but are not actually boolean values. In spreadsheet logic, `TRUE` (the boolean) and `"TRUE"` (the text) are two different things, and COUNTIFS treats them as such. The fix is not to keep switching between quotes and no quotes; it is to check whether the cell values are stored as text or as logical values.
For anyone who has spent time wrangling data in traditional spreadsheets, this moment of confusion is painfully familiar. The root cause is almost always invisible formatting or data type mismatches hidden beneath what you see on screen. When you type `TRUE` into a cell, the software may interpret it as text if the column is formatted as "Text" or if the value was imported from another source. The simplest test is to use `=ISTEXT(K2)` on a sample cell. If it returns `TRUE`, your "TRUE" is text, and you need `COUNTIF(K:K,"TRUE")` with quotes. If it returns `FALSE`, then the cell contains a boolean, and you can use `COUNTIF(K:K,TRUE)` without quotes. The user's screenshot shows column K with what appears to be text, but the only way to know for sure is to check the underlying data type.
This is not a flaw in your workflow; it is a limitation of tools that treat data types as an afterthought. Traditional spreadsheets force you to manage these invisible distinctions manually, and when they break, debugging feels like chasing ghosts. The practical takeaway here is that your time is better spent on analysis than on diagnosing why a simple count fails. An AI-native spreadsheet would handle this automatically, recognizing that `TRUE` and `"TRUE"` should be treated as equivalent when counting, or at minimum surfacing a clear warning that a data type mismatch exists. Until then, the fix is straightforward: use `=COUNTIF(K:K,"TRUE")` if your values are text, or convert the entire column to booleans with `=K2="TRUE"` in a helper column. That single change will turn your zero into the count you expected all along.