Most Shopify audit tools give you a polite report.
Vetta roasts your store instead and tells you exactly how to fix what's broken.
A few weeks ago, I built Vetta an AI-powered tool that audits Shopify stores for conversion issues.
Instead of a standard “here are some insights” report, it bluntly calls out where your store is bleeding money, then gives you actual solutions to fix it.
I built the first version in a single session using Emergent.sh.
The core functionality was there, the app was running, and I could get surprisingly far without building everything from scratch.
But there was one problem:
The interface worked, but I wasn't completely happy with where it was. I wanted more control over the design and the ability to iterate without constantly spending tokens.
So instead of continuing to spend tokens on changes I knew I could eventually handle myself, I decided to take a different route.
I deployed the code to Git and started working on it directly.
That shift has been interesting.
Emergent helped me get from idea → working product quickly.
Git and my own development workflow give me more control over what happens next which matters a lot for a project where the tone and design carry as much weight as the logic behind it.
I'm still learning the codebase and figuring things out as I go, but that's kind of the point of this project.
I'm not trying to build the perfect app on the first attempt.
I'm trying to understand what I can build, where AI can accelerate the process, and where I still need to get my hands dirty.
Vetta started as an AI-built project. Now I'm turning it into a project I actually understand.
Top comments (1)
Taking the tool back into your own hands is a good instinct when the output affects trust. AI can be useful for the first audit pass, but ecommerce recommendations need context: margin, catalog reality, brand voice, and which changes a store owner can actually implement this week.