
Design engineering has always lived between design and code. But with AI tools turning prompts into interfaces and code into editable canvases, that bridge is becoming a new way of building.

A three-week mobile banking project taught me that the “proper” UX process is not always realistic. Sometimes, the better approach is to work with what you know, identify what you still need to learn, and make the strongest decision possible under real constraints.

A/B testing compares two versions of a design to see which performs better with real users. Here’s how UX teams can use it to test hypotheses, measure outcomes, and make smarter product decisions.

This case study shows how one ad experience redesign increased total ad exposure while lowering perceived friction, proving that timing and context can matter more than raw interruption.