Rakuten has achieved a transformative overhaul of its software development process by integrating Anthropic’s Claude Code, resulting in the following significant outcomes:
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Claude Code demonstrated autonomous programming for up to seven continuous hours in complex open-source refactoring tasks, achieving 99.9% numerical accuracy;
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New feature delivery time was reduced from an average of 24 working days to just 5 days, cutting time-to-market by 79%;
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Developer productivity increased dramatically, enabling engineers to manage multiple tasks concurrently and significantly boost output.
Case Overview, Core Concepts, and Innovation Highlights
This transformation not only elevated development efficiency but also established a pioneering model for enterprise-grade AI-driven programming.
Application Scenarios and Effectiveness Analysis
1. Team Scale and Development Environment
Rakuten operates across more than 70 business units including e-commerce, fintech, and digital content, with thousands of developers serving millions of users. Claude Code effectively addresses challenges posed by multilingual, large-scale codebases, optimizing complex enterprise-grade development environments.
2. Workflow and Task Types
Workflows were restructured around Claude Code, encompassing unit testing, API simulation, component construction, bug fixing, and automated documentation generation. New engineers were able to onboard rapidly, reducing technology transition costs.
3. Performance and Productivity Outcomes
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Development Speed: Feature delivery time dropped from 24 days to just 5, representing a breakthrough in efficiency;
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Code Accuracy: Complex technical tasks were completed with up to 99.9% numerical precision;
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Productivity Gains: Engineers managed concurrent task streams, enabling parallel development. Core tasks were prioritized by developers while Claude handled auxiliary workstreams.
4. Quality Assurance and Team Collaboration
AI-driven code review mechanisms provided real-time feedback, improving code quality. Automated test-driven development (TDD) workflows enhanced coding practices and enforced higher quality standards across the team.
Strategic Implications and AI Adoption Advancements
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From Assistive Tool to Autonomous Producer: Claude Code has evolved from a tool requiring frequent human intervention to an autonomous “programming agent” capable of sustaining long-task executions, overcoming traditional AI attention span limitations.
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Building AI-Native Organizational Capabilities: Even non-technical personnel can now contribute via terminal interfaces, fostering cross-functional integration and enhancing organizational “AI maturity” through new collaborative models.
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Unleashing Innovation Potential: Rakuten has scaled AI utility from small development tasks to ambient agent-level automation, executing monorepo updates and other complex engineering tasks via multi-threaded conversational interfaces.
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Value-Driven Deployment Strategy: Rakuten prioritizes AI tool adoption based on value delivery speed and ROI, exemplifying rational prioritization and assurance pathways in enterprise digital transformation.
The Outlook for Intelligent Evolution
By adopting Claude Code, Rakuten has not only achieved a leap in development efficiency but also validated AI’s progression from a supportive technology to a core component of process architecture. This case highlights several strategic insights:
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AI autonomy is foundational to driving both efficiency and innovation;
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Process reengineering is the key to unlocking organizational potential with AI;
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Cross-role collaboration fosters a new ecosystem, breaking down technical silos and making innovation velocity a sustainable competitive edge.
This case offers a replicable blueprint for enterprises across industries: by building AI-centric capability frameworks and embedding AI across processes, roles, and architectures, organizations can accumulate sustained performance advantages, experiential assets, and cultural transformation — ultimately elevating both organizational capability and business value in tandem.
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