"I was spending more time learning tools than learning myself."
When AI tools started taking off, I tried to keep up.
Every week brought a new “game-changing” app, plugin, or prompt technique.
I jumped between them, curious but restless — always looking for the next shortcut to better work.
At first, it felt productive.
But after a while, everything started to blur together.
The results looked good, but not mine.
Fast, efficient, and forgettable.
That’s when I realized I was spending more time learning tools than learning myself.
AI wasn’t the problem — my approach was.
I was treating it like a race instead of a process.
"AI isn’t a race to keep up with — it’s a process to grow through."
So I stopped chasing AI trends and started teaching it my taste instead.
Not to make it sound like me, but to help it understand what felt right to me.
I started giving AI direct feedback — what felt right, what didn’t, and why.
Each time something felt off, I told it why.
Each time it clicked, I saved that moment as a reference.
Over time, those choices formed a quiet language.
And surprisingly, AI began to reflect it back.
The more I used it, the more it acted like a mirror — showing patterns I didn’t know I had.
In trying to teach AI my taste, I ended up discovering it myself.
"The more I used it, the more it acted like a mirror — showing patterns I didn’t know I had."
Now, I don’t rush to try every new tool.
I go deeper with the few that understand me.
Because building with AI isn’t about having the newest thing.
It’s about creating something that feels true.
And the more I refine my taste, the less I need to prompt.
I don’t chase trends anymore.
I just build from what resonates.