Improving work with AI

An era where what comes out fast is a working prototype, not a static screen. I delegate repeating work to AI and keep improving it at the individual, squad, and company level.

View the Korean AI Work page

In use

A translator between teams

What the engineering team is doing is hard for other teams to follow. I designed an environment that translates each person's code output, so anyone can pick up the context without technical knowledge.

In use

Backlog management automated from Slack

Daily scrums, backlog items, customer issues and milestones are collected from Slack and extracted automatically so none of them go missing. It removes the manual sorting and keeps the process sustainable.

In use

Translation automation

Every term that gets added has to be matched across seven languages, not one. I built a process where the system, not a person, translates what is missing and keeps terms that already exist consistent.

In use

Designing and improving the admin tool

A spec that actually runs, and a prototype at the same time. Internal staff use it before anything reaches customers, so we can check whether a feature works, and it is designed to be the admin the training team uses in real work.

In use

Property level information in one place

Scattered records are grouped by property, so they become information the team can actually use for customer support and training.

In use

Usage environment analytics pipeline

User OS, screen size and mobile environment become the analytics foundation for product decisions. I built a pipeline that collects what we need through Clarity, GTM and GA4.

In use

Policy and screen spec management

PRDs, policy documents and screen specs are kept in one place. Slack threads and Notion pages are cross-checked so every requirement has a source on record. At feature kickoff it is what we open to settle policy and see the prototype concept.