Min-Hee Chen.

Min-Hee writes about applied AI inside operating companies — unit economics, evaluation, and the workflow rewires that decide which models actually stay in production. Previously an applied scientist before going independent.

Filed dispatches

02 / AFTER-ANNOUNCE

LLMs in Local Dialect: The Localization Frontier.

Why the most defensible AI products in SEA are not the largest models, but the ones that hear the customer correctly.

Min-Hee Chen · 9 Min

04 / FRAMEWORKS

Retention Systems That Survive Scale.

Why every retention model breaks at $5M ARR, and what to build before it does.

Min-Hee Chen · 10 Min

02 / AFTER-ANNOUNCE

AI Unit Economics: The Margin Test Most Startups Fail.

A pragmatic look at gross margin compression in AI-native products, and where the next defensible 30 points come from.

Min-Hee Chen · 12 Min

02 / AFTER-ANNOUNCE

The Real Cost of a 'Free' Internal Copilot.

A line-by-line breakdown of the inference, eval, and human-review spend from a six-month internal rollout that started as a free pilot.

Min-Hee Chen · 10 Min