Blogs

TestGenX is an AI-native test automation tool designed to help QA teams automate testing at the speed of modern development. With no-code test creation, AI-driven maintenance, and parallel execution, it ensures fast, reliable tests for AI-powered applications.

If you’ve been following the AI space, you’ve likely heard the buzz around evals. Industry leaders agree that evaluating LLMs is key to building effective AI products. As AI continues to grow, learning how to run evals will become a must-have skill for QA professionals, product managers, and developers

The article explores the top test automation trends to watch in 2025, emphasizing the growing importance of AI-powered testing, low-code/no-code platforms, shift-left testing, and cloud-based solutions. It highlights the need for seamless integration with DevOps and CI/CD pipelines to enhance software quality, efficiency, and adaptability in the evolving software development landscape.

Validation testing is a critical process that ensures systems meet the highest standards of performance and reliability. By understanding the key types of validation testing, the phases involved, and the best practices to follow, businesses can enhance data quality, support decision-making, and prevent costly errors.

APIs are everywhere, quietly powering the apps and services we use daily. They allow seamless communication between software, forming the backbone of modern applications. However, if your APIs fail, your business eventually fails. Therefore, API testing becomes important as it checks for secure, high quality and integrated software.

The "Ghibli Trend" wasn't just another online craze — it became a live performance and load-testing scenario for OpenAI. Social media users began sharing Ghibli-inspired AI images, creating a massive buzz.

Flaky tests show inconsistent results across runs. They create unreliable outcomes, hurting test accuracy. These tests may report false positives or negatives. False negatives flag non-existent defects, wasting time.

Generative AI applications such as ChatGPT excel at making conversations, creating jokes, writing texts, and providing programming assistance, but how do we make sure they’re smart, safe, and fair?

In the rapidly evolving landscape of software development, QA teams never stop searching for means to optimize testing efficiency without losing precision. Playwright Model Context Protocol (MCP) has a new paradigm that is revolutionizing automated testing.

APIs power everything—from your favorite apps to critical business systems. But what happens when your API is subjected to large or unexpected traffic, security threats, or plunges under load? One weak link can destroy UX, destroy data or take down your service.