Pratik Patel

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.

With TestNG.xml, you can run multiple test cases in one go, control execution flow, and even group tests based on priority. No more manually triggering tests—just set it up once and let it handle everything for you.