Systems | Development | Analytics | API | Testing

May’s release brings significant strides in browser support, cross-platform test execution, and intelligent AI-powered enhancements. Whether you’re running large-scale cloud tests, fine-tuning user journey maps, or adapting to Chrome’s latest changes, Katalon continues to innovate with features that boost precision, observability, and test coverage. Here is what we delivered in May.

Insurers today face intensifying pressure on multiple fronts. Operating margins have compressed by as much as 3 percent over the past five years, driven by deteriorating loss ratios, sustained inflation, and escalating competition from insurtech challengers. At the same time, legacy infrastructure and fragmented delivery models continue to hinder responsiveness, with product development cycles still exceeding 12 months for many carriers.

Insurers are facing tighter margins, rising costs, and pressure to modernize, which are all challenges that traditional levers alone can no longer solve. Amidst the struggle, Generative AI offers a breakthrough. With the potential to add $2.6 to $4.4 trillion annually to the global economy, which is higher than the UK’s GDP, it can redefine how insurers create value.

Recently, I had the pleasure of sitting down with Cristiano Caetano, VP of Product at Katalon, to explore his journey in software testing, a path that began with frustration, evolved through innovation, and now looks toward an exciting AI-driven future. Cristiano's insights shed light not only on his personal career path but also on the broader evolution and future of software testing.

The G2 Summer Report 2025 has arrived. Published by the renowned software review website g2.com, this report brings value to both sides of the market: With up to 37 G2 badges received this time, we're really happy to see that our product is resonating with users across a wide range of markets and industry segments, including DevOps, Software Testing, and Automation Testing. Here's a quick recap of the report.

Regression testing is indeed one of the most time-consuming part of software testing: repetitive, tedious, and requiring high volume of executions. And yet, you can't ignore regression testing. It is the guardrail preventing bugs from slipping into production. But if you don't try to reduce the time it takes to do regression testing, it becomes counter-productive, very soon.

With the rapid adoption of AI-driven coding tools, software development is experiencing a seismic shift. Increasingly, developers rely on tools like GitHub Copilot and other generative AI solutions (collectively termed “vibe-coding”) that now account for roughly 30% of code output in leading organizations. This trend raises significant questions for QA teams: What happens when AI significantly contributes to the codebase, and how does this reshape the landscape of software testing?