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.

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

Build faster (“Speed!! Speed!! Speed!!”): Teams use Codex in operational workflows, including KQL-based monitoring and diagnosis, to accelerate root-cause analysis and remediation, helping compress MTTR by up to 50%.

Build safer (“Get things done”): Codex is invoked in CI/CD for code review and vulnerability checks, applying internal standards automatically so teams can ship quickly with guardrails.

Operate smarter (“AI-nization”): Codex drives larger, ambiguous projects forward from specification toward working implementations, reducing dependence on perfectly-defined requirements, enabling more autonomous execution, and ultimately compressing quarter-long efforts into weeks.

Source link