Rakuten fixes issues twice as fast with Codex

Rakuten⁠⁠(opens in a new window) is a global innovation company operating across e-commerce, fintech, and mobile communications, serving both consumers and merchants at massive scale. With 30,000 employees worldwide, its engineering teams ship across a large, complex product ecosystem where both speed and reliability are essential.

That’s why Yusuke Kaji, General Manager of AI for Business at Rakuten, has spent the past year pushing agentic workflows deeper into how teams plan, build, and validate software. Codex⁠⁠—the coding agent from OpenAI—has become a core part of Rakuten’s engineering stack, especially where the company needs to move faster without compromising security.

Over the past year, Rakuten engineers have used Codex across operations and software delivery to compress incident response (including a ~50% reduction in mean time to recovery, or MTTR), strengthen CI/CD with automated code review and vulnerability checks, and support more autonomous development on complex projects.

“We don’t just care about generating code quickly. We care about shipping safely. Speed without safety is not success.”

—Yusuke Kaji, General Manager of AI for Business

Inside the rollout

Inside Rakuten’s engineering team, their AI agenda is crisp and intentionally operational. Kaji frames the work around three priorities that teams rally behind:

Codex maps directly to each priority as a dependable agent in a broader toolkit, showing up where speed, safety, and autonomy create compounding value.

Building faster by compressing incident response

Speed at Rakuten includes recovery time, not just development velocity.

Teams use KQL (Azure’s query system for logs and telemetry) to monitor APIs and analyze signals. Codex works alongside these workflows to help identify root causes and suggest fixes, reducing the time between alert and resolution.