The user who posted that question on Reddit isn't alone. When a macro that once ran smoothly suddenly crashes your computer, the frustration is real and the instinct is to hunt for a fix in the same tool that broke. But that instinct points in the wrong direction. The real takeaway here isn't about debugging VBA or chasing down a query update glitch. It's about recognizing when a tool has reached its limit.
Macros were a clever workaround for a world where spreadsheets couldn't think. You wrote a script to automate a repetitive task, and it worked, until the spreadsheet grew, the data source changed, or an update silently rewrote the rules. Now you're spending hours trying to restore something that was never designed to adapt. That's not a failure of your skill. It's a constraint of the tool itself. Traditional spreadsheets treat data like a static snapshot, and macros are brittle instructions that assume nothing will change. When something does, the whole house of cards collapses.
What this means for you is a choice: keep patching a legacy system, or explore a smarter path forward. AI-native spreadsheets don't rely on fragile scripts. They understand your intent, handle query updates dynamically, and adapt to changes without crashing your machine. Instead of writing a macro that might break next quarter, you describe what you need in plain language, and the tool executes it consistently. The time you currently spend troubleshooting macros could be time spent actually analyzing your data and making decisions.
The practical shift is this: stop asking how to fix a broken macro. Start asking what your workflow would look like if the tool did the heavy lifting for you. The user who posted that question deserves a solution that doesn't require a second job in maintenance. The answer isn't a better macro. It's a spreadsheet that doesn't need one.