Insight · Plateer AI Labs

Article series

The GS Certification Diary

Three weeks of reading 80 defect reports and rebuilding the code, the errors, and the manual

5 articles

The Harness Diary

Designing the execution environment an AI agent works in, from the ground up

10 articles

The Ontology Diary

Starting from the questions, building a knowledge graph, then working on quality and search

10 articles

All articles

XGEN Preview2026.07.06

XGEN has been awarded Grade 1 GS certification

The XGEN Agentic AI Platform received Grade 1 — the top grade in Korea's national software quality certification. What it means, and what it changes.

PPlateer AI Labs

Tech NoteThe Harness Diary2026.07.01

Designing tool exposure and output delivery as execution context (Part 9)

Exposing connected tools search-first, and separating what the model is told about an output destination from who owns actually delivering to it.

김진수

Tech NoteThe Ontology Diary2026.06.30

Adapting extraction batch size to the model's limits (Part 9)

Computing the context and output budgets together, then splitting and reprocessing only the batches that timed out or came back as truncated JSON.

김진수

Tech NoteThe Ontology Diary2026.06.24

Why ten CSV classes became four (Part 8)

Persisting generation provenance so post-processing cannot rewrite a structured schema, and computing reprocessing scope from the last completed build.

김진수

Field Report2026.06.23

AI agents in retail: from reading documents to carrying out the work

A discussion with H, a retail and media company, on adopting AI agents — connecting document OCR to usable business data, why product-code generation is a reasoning problem, when fine-tuning is not required, and how to carry a PoC into production.