Systems | Development | Analytics | API | Testing

Agentic testing isn’t just about faster execution - it’s about uncovering what’s missing from your test suite. This blog explores a forward-looking model where AI agents help identify gaps in traditional, deterministic systems through techniques like scenario delta detection, data condition surfacing, edge path exploration, and test case obsolescence tracking.

Today, Gartner released the first-ever Magic Quadrant for AI-augmented Software testing, and I’m very excited to share that Katalon has been named a Visionary!

When working with web automation in Python, knowing how to get the current URL is essential. It helps you confirm where the browser is, catch unexpected redirects, and make sure your test steps behave as expected. The command driver.get("url") is what takes you to a page. But after that, how do you check if you're on the right one? That’s where driver.current_url comes in.

When writing automated tests with Selenium WebDriver and Python, one common task is dealing with input fields that already contain text. Whether you're working with a login form, a search bar, or a multi-step checkout flow, starting with a clean field helps ensure consistency every time your test runs. The clear() method in Selenium offers a direct way to remove any existing text inside a form field before you input new data.

When you think about test automation, what image comes to mind? For many QA leaders, automation still means running the same scripts every night, chasing down false-positives, and fighting maintenance debt. That model served us well for a while, but it was always limited: automation only runs what humans script. The next era is about AI-powered testing. AI-powered testing doesn’t just execute predefined tasks; it generates coverage dynamically, adapting as your application evolves.

Traditional test scripts are too brittle for today’s fast-moving, complex systems. AI-powered agents enable a shift to scenario-based testing - high-level, reusable flows that describe user intent and behavior. Agents can help extract, generate, and evolve these scenarios, while humans guide relevance, risk, and validation. This approach improves stability, cross-platform coverage, and business alignment.