Boosting API Automation at Angkas with Cursor AI

With over 500 test cases spanning diverse REST APIs, Angkas faced increasing friction  using traditional approaches to automation.  While Rest-Assured enabled robust API testing, manual implementation presented several limitations:

• Repetitive code creation: Writing boilerplate for similar API endpoints (headers, payloads, assertions) led to redundancy and increased maintenance overhead.
• High manual effort: Developers spent considerable time building tests from scratch, creating utilities, and managing data setups manually.
• Fragmented workflows: Maintaining consistency across multiple files and modules required constant context-switching and manual updates, slowing down overall test development.

To overcome these challenges, the project team evaluated multiple AI-assisted development tools — including GitHub Copilot — and ultimately chose Cursor AI, a full-featured IDE built on top of VS Code, for its deep project awareness, seamless integration, and strong alignment with the team’s test automation needs.

Key capabilities leveraged:

• Inline AI chat: Developers can highlight code and prompt intelligent suggestions in context.
• Project-aware code generation: Cursor adapts to framework patterns and naming conventions.
• Efficient refactoring: Repetitive logic is streamlined with minimal manual effort.

This allowed Angkas to shift from patchwork automation to a more intelligent, scalable, and maintainable test framework .

By leveraging Cursor AI’s capabilities, Angkas expects to achieve 30–50% faster onboarding and automation for new APIs.

Improvements delivered:

• Reduced manual effort through project-aware code generation.
• Minimized copy-paste cycles led to better developer workflow and reduced context-switching.
• Consistent and scalable test architecture for 500+ API test cases.
• Improved refactoring and framework maintenance across multiple modules.