Wanjia (Rebecca) Ruan阮琬珈 (Rebecca) I study how AI shapes trust — then I build with it anyway. 研究AI如何影响信任——然后依然选择用它来构建。

I didn't start with AI.
I started in brand marketing — coordinating clients, KOLs, and vendors,
chasing billion-impression metrics that looked great on paper.
But I wanted to make something real, not build my sense of achievement on others' work.

我并非一开始就是AI Native。
最初的兴趣落在品牌营销——如何将好的产品被大家看到是我的目标。
工作中客户、KOL、供应商，各样的声音交织在一起，
一同追逐着那些在报告里闪闪发光的数字。
但我想做点自己的产品，而不是把成就感寄托在他人的作品上。

So I quit and went to grad school.
I wanted to see what happens when you combine communication —
something I'm good at — with the cutting edge of data science and AI.
I absorbed knowledge from every direction: how LLMs shape perception,
how human-AI interaction works, where AI fails in specific contexts,
how the systems we're building actually operate.

于是我辞职，去读研。
我想看看，我擅长的沟通与语言和人文理解，
遇见数据科学和AI这些时代最前沿的技术，会迸发出怎样的火花。
我像海绵一样多维度地吸收着：从最基础的机器学习到晦涩的大模型知识，
理解LLM如何重塑认知、感受人机交互的微妙平衡、研究AI在特定情境下的失灵时刻。
一步步清楚我们正在构建的这些系统和世界的多维，清楚它们真实的运作方式。

But I don't just study — I build.
I get my hands dirty, turning ideas into products based on real insights,
not hype. Leading teams through the messy process of vibe coding
and iteration, shipping features users actually need —
not just features the model can produce.

但我不止于研究——我还要亲手构建。
把想法变成真实的产品，拒绝HYPE，将基于日常洞察去理解、剖析、研究、整理。
带着团队在vibe coding和迭代的混沌中摸索前行，抽丝剥茧。
最重要的是，交付那些用户真正需要的功能——
而不是模型恰好能做出来的功能。

The best AI products are built by people who've seen both sides —

who've written marketing decks and read research papers,
conducted user interviews and debugged AI failures.
You need to understand people and communicate well,
while also understanding the tech deeply enough to know what's possible.

That's the kind of PM I'm becoming.

最好的AI产品，诞生于见过两面的人手中——

写过让人心动的营销文案，做过深入的用户访谈，懂人构建的社会；
啃过晦涩难懂的学术论文，手搓也debug过代码，实践着新技术；
在人文和技术的交织处，学习人与AI的交互，也理解LLM在哪些时刻会悄然失效。

懂人、善于沟通，也要足够深入地理解技术，知道什么是真正可能的。
这，就是我正在成为的那种PM。