What I Learned After Letting Different AI Models Refactor the Same Function

I had a function that bothered me. Not broken—just inelegant. 200 lines of nested conditionals handling user permissions across three different access levels with special cases for admin overrides and temporary grants. It worked. Tests passed. But every time I looked at it, I knew it could be better. So I did something unusual. I asked five different AI models to refactor it. Same function, same context, same instruction: "Make this better." What I got back revealed something fundamental about how different AI systems think about code—and exposed assumptions I didn't know I was making about what "better" even means. The Function That Started It The original code looked like this (simplified for clarity): function checkPermission ( user , resource , action ) { if ( user . role === ' admin ' ) { return true ; } if ( user . temporaryGrants ) { const grant = user . temporaryGrants . find ( g => g . resource === resource && g . action === action && new Date () < new Date ( g . expiresAt ) )