Speaker of TestIstanbul 2025
Software Engineering Lead @Dataroid | QA Automation Expert
Speech: AI-Powered Test Automation: Transforming Testing Workflows with Cursor AI & MCP
This session explores how modern QA teams can transform their test automation workflows using AI-powered tools like Cursor and architecture frameworks such as Model Context Protocols (MCP). Drawing from real-world implementations, the session offers practical insights and design strategies for scaling intelligent testing across API, web, and SDK domains.
It begins with a comparison of pre-AI and post-AI test automation pipelines, identifying key inefficiencies that large language model (LLM)–enhanced solutions help to resolve. A detailed walkthrough follows, showing how Cursor Rules are structured—from user intent and project conventions to feature-specific logic.
The presentation introduces the MCP architecture, which modularizes context handling, rule execution, and memory integration across distributed repositories. This enables more maintainable, explainable, and reusable test logic, shifting QA teams from static scripting toward dynamic, context-aware validation.
A live demo showcases:
- AI-generated test steps and rule chaining
- Contextual API documentation validation
- Seamless rule deployment across multiple microservices
- Key lessons learned include the need for robust context management, validation safeguards for
- LLM output, and recovery mechanisms to protect quality gates in CI/CD pipelines.
The session concludes with a look ahead at ongoing work—standardizing test requirements, building a project-wide test knowledge base, and aligning AI-enhanced tooling with engineering workflows.
Ideal for QA engineers, test architects, and engineering leads aiming to responsibly integrate LLM-powered automation into real-world test infrastructure.
About Sadi Önal
A Software Engineering Lead with over 14 years of experience in software testing and test automation. He currently leads the automation team at Dataroid, focusing on improving efficiency and quality across testing workflows.
With a strong interest in leveraging AI for software quality, he actively explores and integrates AI-based solutions—including agents, copilots, and rule-based systems—to enhance the speed, scalability, and precision of test processes. While tools like Cursor and MCP have been part of recent implementations, his broader focus is on evaluating and adopting emerging technologies that improve software development and testing outcomes.
His experience spans large-scale transformation projects across finance, aviation, and analytics domains. He combines technical depth with a pragmatic leadership style, continuously seeking ways to optimize engineering workflows through automation, data, and intelligent tooling.
