You know that feeling when you ask an AI to write some code and it gives you three different versions instead of one
My first reaction was honestly annoyance like why can’t it just give me the right answer the first time
But then I started seeing something interesting happening
When I had multiple options to choose from I found myself actually thinking more deeply about what I really wanted
It reminded me of that principle about treating code as capability while intentions and interfaces become our long-term assets
Think about it when you’re presented with several working solutions you stop focusing on the code itself and start focusing on which approach best matches your actual needs
You begin to see patterns in what works and what doesn’t
You develop a better sense of what makes a good prompt versus a mediocre one
I remember working on this data processing script where I kept getting variations that all technically worked but each had different tradeoffs
One was super fast but used more memory
Another was memory efficient but slower
A third was beautifully readable but less optimized
Having these options forced me to clarify what mattered most for this specific use case
Was this script going to run in a memory-constrained environment
Would other developers need to understand and modify it later
These are the kinds of questions that get you thinking at the intention level rather than just the implementation level
Over-generation essentially turns coding into a conversation
Instead of a single answer you get a discussion about different approaches
You learn what your AI assistant considers important enough to vary
You start to understand its design sensibilities
And most importantly you become more intentional about your own choices
This aligns perfectly with the shift toward viewing code as disposable while our prompts and specifications become the valuable artifacts we maintain
The real magic happens when you start using over-generation deliberately
Ask for multiple approaches to the same problem
Request implementations with different priorities
Get variations that emphasize different qualities
Then compare them side by side
What makes one version better than another
Which one feels right for your current context
This process trains your intuition for what makes good software in different situations
It’s like having multiple experienced developers giving you their take on the same problem
Each with their own biases and strengths
Your job becomes curating rather than creating from scratch
You’re the editor not the writer
The director not the actor
This is where vibe coding truly shines
When you stop worrying about writing perfect code and start focusing on making perfect choices
When the quality of your decisions matters more than the quantity of your keystrokes
So next time your AI gives you more than you asked for don’t get frustrated
See it as an opportunity to refine your intentions
To clarify what really matters
And to build that muscle for making better software decisions
Because in the end that’s what separates good developers from great ones
Not how much code they write but how well they choose which code to use