This user's problem is a perfect illustration of why traditional spreadsheets have reached their limit. They have a formula that works, but the tool itself refuses to scale with them. Dragging down a formula should be the simplest of tasks, yet here it requires manually editing a table reference 250 times. That is not a workflow. That is a punishment.
The core issue is that Excel treats each table as a fixed object. When you write `Table_1`, you have locked yourself into a single data range. The software offers no native way to say, "I want this formula to apply to the next table in a sequence." So users like u/dand06 resort to copy-paste-edit, a repetitive chore that invites errors and wastes hours. The formula itself is clever, using `SUM` with `IF` to match a criteria and sum a column, but the tool fails at the very point where automation should shine. You should not have to fight the tool to repeat a pattern.
What this reveals is a deeper design flaw: spreadsheets were built for static analysis, not for dynamic, repetitive tasks across many tables. The user's request is modest, increment a table name by one, but it exposes a gap between what people need and what legacy tools deliver. When you have 250 tables and a formula that must be replicated across all of them, the spreadsheet becomes a bottleneck rather than an accelerator.
An AI-native approach would solve this differently. Instead of forcing the user to manually edit each reference, the system would recognize the pattern and offer to apply the formula across the entire sequence. The formula itself could be written once, with a placeholder for the table index, and the AI would handle the rest. The user's time would be spent verifying results, not performing data entry. That is the shift we should demand: moving from a tool that requires manual repetition to one that understands intent.
The practical takeaway is simple. If you find yourself doing the same edit hundreds of times, the tool is failing you. Stop accepting that as normal. Explore solutions where the software adapts to your logic, not the other way around. The future of data work is not about grinding through 250 manual edits, it is about writing the logic once and letting the system do the rest. That future is already here for those willing to look.