AI product ownership
Problem selection, prototype scope, quality and operating conditions.
SEOKMO GU · AI PRODUCT & OPERATIONS
I turn AI, data, product, and operations into work a team can actually run.
I have worked across distributed-systems research, logistics and commerce operations, data products, and generative-AI product work. My focus is making the next decision concrete: what problem to solve, what evidence is needed, and who can operate the result.
Data to product
Data quality, decision rules, and customer-facing systems.
Operations & automation
Making recurring work visible, dependable, and easier to run.
Selected work
Work with a public, bounded record
Each link leads to a Korean evidence page. Internal product details, unverified metrics, and confidential material are intentionally excluded.
- 01 · AI PRODUCT & AX
Choosing AI problems worth building
I compare user change, available data, quality, cost, and operational ownership before turning an AI request into a prototype scope.
Read the Korean evidence record → - 02 · COMMERCE OPERATIONS
Making four sales channels work as one operating flow
As a founder, I aligned order, inventory, settlement, inspection, and shipping work into a shared operating structure and automation routines.
Read the Korean evidence record → - 03 · DATA PRODUCT
Turning city data into product rules
I connected data collection, quality decisions, pricing rules, and a user experience for a spatial-economy product.
Read the Korean evidence record →
Other requests
Speaking, workshops, and early-stage advisory requests can also be discussed when they relate to my product, data, or operations work.
Korean is the source language for the full public record. View the Korean source →