This user's problem is a perfect illustration of why traditional spreadsheets are no longer the right tool for modern data work. When you have to ask, "Can I make 7 columns behave like 8 without breaking the layout?" the tool has already failed you.
The core tension here is obvious: a calendar naturally demands a column for each day of the week, but the data underneath requires an extra column for context, notes, or categories. In Excel or Google Sheets, you are forced into a compromise. You can merge cells, hide columns, or resize manually, but all of those workarounds create fragile spreadsheets that break the moment someone adds a row or adjusts a date. The user's frustration is not a failure of their spreadsheet skills. It is a failure of the spreadsheet's rigid grid model.
Our position is straightforward: the question should not be "How do I force 7 columns to look like 8?" The question should be "How do I design a data structure that adapts to my workflow?" That is where AI-native tools offer a genuine advantage. Instead of fighting column widths and merged cells, you can define the relationship between your calendar data and your supporting data as a flexible layout. The AI understands that a calendar row and a notes row are part of the same logical block, even if they require different column counts. It can dynamically adjust column widths, hide or show fields based on context, and present the view that matches your intent without manual formatting hacks.
For the user who posted this, the practical takeaway is this: the workaround you are searching for is a symptom, not a solution. Every hour spent wrestling column widths is an hour not spent analyzing the data those columns contain. The real opportunity is to explore tools that treat your data as a flexible structure rather than a fixed grid. When the software adapts to you, you stop asking how to make columns fit and start asking what the data is telling you. That shift is the entire point.