When testing new tech features, I follow a structured but flexible approach. First, I research the feature’s purpose and expected outcomes to understand what problems it’s solving. Next, I set up a controlled test environment so I can experiment without affecting production. I start with small, targeted test cases to validate core functionality, then gradually scale to edge cases and stress tests. Along the way, I document results and compare them against benchmarks or existing solutions. Finally, I gather feedback from both users and team members, and I iterate based on what I learn. This approach ensures I’m not just testing functionality, but also usability, scalability, and integration with the broader system

I leverage AI-powered productivity and coding tools to streamline development and operations. Using GitHub Copilot, Tabnine, and ChatGPT (OpenAI API), I accelerate coding, debugging, and prototyping across full-stack projects. For workflow optimization, I apply Notion AI and Zapier AI integrations to automate documentation, task management, and cross-app processes. Additionally, I integrate Terraform with AI support to enhance Infrastructure as Code, ensuring efficient, scalable, and reliable cloud deployments

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