One AI lesson that surprised me: the model wasn't the biggest factor

When I first started experimenting with Ai workflows, I spent most of my time thinking about which model to use and how to write better prompts.

Over time, I realized that neither of those had the biggest impact.

The quality of the information reaching the model seemed to matter much more than I expected. When the input was organized around the actual task instead of simply providing more data, the responses became noticeably more consistent.

It completely changed how I think about building ai applications.

For those learning or building with it:

What has had the biggest impact on the quality of your results?

Could it be:

• Better prompts?
• Better context?
• Better workflows?

Or something else entirely?

I'd love to hear what experience has changed the way you build with it.