ALAN LU

I’m a Senior Product and UX Designer with more than eight years of experience designing digital products across B2B SaaS, AI-powered creative tools, advertising technology, PropTech, FinTech, mobile services, and other complex product environments.

I started my career closer to web development than product design. Although I enjoyed building products, I became increasingly interested in what happened on the other side of the screen: how people understood a product, how they interacted with it, and why something that worked technically could still be difficult or frustrating to use. That curiosity led me into product and UX design, while my development background continued to influence how I work today. I’m technically fluent enough to discuss feasibility, component logic, system states, and implementation tradeoffs with engineers. This helps me connect design intent with how products are actually built, without losing sight of the user experience.

My career has also taken me through different cultures, industries, and working environments in China, Taiwan, and distributed U.S. teams. Those experiences taught me to adapt quickly, listen to different perspectives, and avoid assuming there is only one correct way to solve a problem. They also strengthened my resilience and made me comfortable learning unfamiliar domains, working through ambiguity, and staying focused when priorities or constraints change.

Much of my recent work has involved simplifying complex systems. At BQool, I have worked on data-heavy advertising and automation products while helping establish a more consistent design system across multiple product lines. At Scriptoplay, I helped shape an AI-native creative platform that guides writers through a structured production workflow rather than relying entirely on open-ended chat.

That work deepened my interest in AI-native product experiences. I design around the realities of AI—uncertain output, processing time, context continuity, user trust, and the need for human judgment. I think carefully about how people preview, compare, regenerate, approve, or recover from AI-generated results, and how AI recommendations can present supporting evidence instead of behaving like an unexplained black box.

I’m interested in AI not simply as a productivity tool, but as a new interaction model. My goal is to make intelligent systems understandable, controllable, trustworthy, and genuinely useful within the workflows where people already make decisions and create value.

Today, I’m at my best when working with product managers, engineers, analysts, researchers, and other designers to make complicated products feel clearer—for both the people using them and the teams building them.