I work with technical AI companies on GTM, market expansion, and partnerships. My path started in engineering and moved into commercialization: understanding the product, reading the buyer, and helping it work in a new market.
When buyer language is unstable, competitors are blurry, and the category is still changing names, I write down the real problem first, then choose the entry point.
A partnership is not “let’s meet.” I look for why the other side should meet now, what can move after the meeting, and how distribution, trust, or capital can connect.
I use AI workflows to speed up research, writing, and review. The tool is not the outcome; the outcome is seeing the important signal faster and missing fewer follow-ups.
Building the first North American commercialization path: buyers, events, partnerships, materials, and revenue signal.
Turning scattered market signals into a ranked opportunity list, so judgment does not stay trapped in chat logs.
Turning engineering records into contribution evidence that can be questioned, reviewed, and discussed.
My base is engineering. Electrical and computer engineering, plus early work at a YC intelligent manufacturing company, trained me to understand both engineering systems and product constraints.
The commercial work came later: GTM, market expansion, and partnerships. That work taught me to read the market and the customer more carefully: who has budget, who is only curious, and which situations are worth pursuing.
So I am not the person for “send a few more emails.” I am better suited to questions like: who should the company meet, how should it explain itself, why now, and how do we turn that judgment into meetings, materials, and shipped outcomes?