Most Shopify Themes Fail Before a Single Line of Code Is Written
Not because the design was bad. Because nobody asked who they were designing for. A short UX research pass before touching Figma changes almost everything downstream.
Technical teardowns on Shopify Plus performance, architecture, and conversion — written from production, not theory.
Not because the design was bad. Because nobody asked who they were designing for. A short UX research pass before touching Figma changes almost everything downstream.
Most Shopify Plus stores run 8 to 12 apps at once, and nobody has audited the list in years. Here's what that's costing you, and where to start.
Merchants come with a feature list. Sometimes the right answer is that none of it moves the needle until you fix what's already broken. Three numbers tell you which.
Shopify natively supports three post-purchase offer levels. That's not a limitation once every accept and decline branches into the next best offer.
Most teams run A/B tests and wonder why the results feel hollow. It's rarely the testing tool. It's that they skipped the two steps before it.
AI search doesn't rank pages the way Google's index used to. It reads them, evaluates them, and picks an answer. Most ecommerce SEO still isn't built for that.
The right question isn't which technology to pick. It's what your store actually looks like: the catalog, the team, and how often marketing needs to touch content.
I say this a lot. It saves time and ships faster. But there's a real decision framework underneath it, and knowing when it stops applying is the actual skill.
Most teams treat engineering as execution. The best teams treat it as a growth function, with a short, specific list of things that turn a sprint into revenue.
Every team eventually chases faster processes and shinier frameworks. The businesses that scale the longest are the ones that treated stability as the actual foundation.
I used AI to design a discount engine handling 4,000+ coupon codes. It didn't replace the architecture work. It just caught weak assumptions before they became expensive rewrites.