I work on strategic GTM, market development, and partnerships for technical AI products — turning buyer signal, ecosystem context, and product depth into positioning, sales conversations, and partner routes.
我做技术型 AI 的 GTM、市场拓展与合作。优势不在“多发几封邮件”，而在听懂产品、读懂买方，判断谁真的有预算、信任和理由，再把判断推进到具体会议、具体材料和具体结果。
Understand where demand, trust, budget, and language break down, then turn that into ICP, positioning, and field priorities.
买方语言不稳定，竞品边界不清，行业还在换词。这个时候我会先把真实问题写清楚，再决定该打哪个入口。
Map the ecosystem partners, investors, events, and operators that can move a buyer conversation forward.
合作不是“认识一下”。我会先判断对方为什么现在要见、见完能换来什么，再把资源、分发和融资机会连起来。
Use AI systems to make research, synthesis, and review faster while keeping the judgment explicit.
我会用 AI 工作流加快研究、写作和复盘，但不把工具当成果。成果是更快看见重点，更少错过该追的人。
How I built early North America GTM around buyers, events, partnerships, and revenue signal.
从零开始做北美商业路径：买方、活动、合作、材料和收入线索。
A venture-studio engine that turns scattered market signals into ranked, auditable opportunities.
把散乱信号做成可排序的机会清单，让判断不只停在聊天记录里。
An AI-assisted contribution intelligence layer — Claude reads commits, methodology stays auditable.
让 Claude 读 commit，再把工程贡献写成可以被反问、被复盘的方法。
I studied electrical engineering in Nanjing, then computer engineering at Duke. Built embedded systems, wrote software, watched friends launch hardware companies. The interesting question was never the engineering — it was always: why do buyers pick this and not that?
That question is harder for technical AI products than for almost anything else. Buyer language is unsettled. Reference architectures shift quarterly. The right partnership in March can be irrelevant by August. Operators who can read that velocity — and pull a CEO into the right rooms — are the ones who keep technical companies on the rails.
That's the lane. Strategic GTM and partnerships for technical AI, with enough engineering literacy to be dangerous, and enough field time to know which signals are real.
如果问题只是“多发几封邮件”，我不是最贵也不是最快的人。这个工作可以交给更标准的销售或外包团队。
如果问题是“公司到底该见谁、怎么讲、为什么现在讲”，我能很快进入现场。技术产品、美国市场、亚洲资源、CEO 判断之间的空白，是我最能发挥的位置。
我在南京读电子工程，后来去 Duke 读计算机工程。工程背景不是过去，而是我理解技术产品、判断买方可信度和写清复杂问题的底层优势。