Chen Liu

In the AI era, the product itself is no longer the moat. The real edge is how deeply a team understands its users, how clearly it sees the business problem, and how quickly it can turn that understanding into a functional product.

I define myself as an AI Builder and Creator. As a Builder, I turn product judgment into demos, agents, and deployed AI products. As a Creator, I package AI services, repeatable solutions, and AIGC content so other people can use the capability.

I started my career in Silicon Valley as a Product Designer, focused on in-house product experience design. Through user research, I kept finding that real problems required product-level thinking — not just design solutions. That pushed me to approach every experience design project by first analyzing product strategy, business direction, and target users before landing on the right design.

Working in big tech, I was too far from the market, the product, and actual users. Moving to design consulting closed that gap. There I worked across product definition, architecture, feature planning, design delivery, and direct client engagement — and started thinking seriously about the business logic behind every product decision.

I leverage AI capabilities to fill in exactly what I need to build. I started with GPT-3 for text generation and Midjourney and Stable Diffusion for image work. Then vibe coding gave me a way to turn ideas directly into working products. As the field kept moving deeper, so did my work: from prompt engineering to understanding model capabilities — and from there, applying multi-model orchestration and different technical architectures to build AI products.

All of that experience has compounded into real products. The AI Presentation Agent is the full capability loop in action — from identifying a user need to building and deploying a commercial product inside a client's platform. The User Research Agent takes that further: using AI to solve a real enterprise problem that most teams don't have the resources to tackle. And the WeChat Article Adapter shows the same instinct applied to my own work — identifying friction in my content workflow and building a tool to remove it.

Through building AI products, I've come to understand something about how I work best. I'm a long-termist — and I'm genuinely obsessed with depth. I like thinking in systems and solving problems with structure. In product terms, that means I want to go deep into one niche market over time, build something that compounds in value, and ideally see a real commercial result from that focus.

That's what's driving the relocation. I'm looking for an environment where deep work is the norm — where I can stay close to users, stay present in the business, and keep building from that depth over the long term. I'm also drawn to cultures that are open and inclusive, where experimentation is encouraged, iteration is expected, and people are genuinely open-minded about new approaches.