Yongjun Chen

Systems and Products

Codex

Evaluated behavior of GPT-6 Astra and upcoming models in Codex across agentic coding, connectors, CUA, and memory/compaction; calibrated reasoning for token efficiency. Iterated toward a secure, reliable eval environment by stabilizing failure-prone runs, shortening evaluation turnaround, and safeguarding long-horizon agent behavior.

Coding agents

Improved coding-agent reliability via context, tools, delegation, and failure analysis; explored training lower-cost subagents with multi-agent RL.

About

working on Codex at OpenAI; previously worked at Augment Code, Apple and Salesforce AI Research; studied Statistics in Wuhan and Computer Science in Washington State.