Systems | Development | Analytics | API | Testing

‍ 2025 is turning out to be a big year for AI agents. Grand View Research notes that the global AI agent development market, worth about USD 5.40 billion in 2024, could soar to nearly USD 50.31 billion by 2030, growing at a remarkable 45.8% CAGR. And it’s not just about numbers. A recent McKinsey report highlights that agentic AI is the next logical step after generative AI. Evolving from simple task execution to actively driving goals and delivering results that make a measurable difference.

You’ve probably been there: your AI coding assistant just generated what looks like a perfect solution to your problem. Decent code quality, reasonable structure, and even some comments. You run it, and… it works. So you ship it. Three weeks later, your production logs are full of 500 errors from edge cases the AI never considered, or worse, you discover the code has been making unvalidated database calls that could have been prevented with basic input sanitization.

We’re excited to introduce two powerful new capabilities in Xray: AI Test Case Generation and AI Test Model Generation for Xray Enterprise, powered by Sembi IQ — Sembi’s AI platform built to help QA, development, and security teams deliver better software, faster. With these new features, Xray brings intelligence directly into the testing process, making it faster to design tests, easier to ensure coverage, more secure by design, and always guided by human expertise.

Hey everyone, Launch days are always exciting, and today, I couldn’t be happier to share something we’ve been working hard on: the MCP Server in Katalon Studio. This isn’t just another update. It’s a milestone for StudioAssist and for all of you who are looking to move faster with AI. With this release, we evolved StudioAssist from simply answering your questions to becoming your Agentic AI assistant. That means it doesn’t just tell you what to do.

To monetize digital content, we have used means like ad networks, affiliate links, and paywalls. However, with the fast and widespread adoption of AI, demand for high-quality data has increased. To make sure Large Language Models (LLMs) models deliver value and accurate results, a wide spectrum of content is often scraped and trained on without permission or compensation. This includes blogs, product and technical docs, forums, and research papers.