Systems | Development | Analytics | API | Testing

How much of your CI runtime is spent waiting on APIs that return the same response every time? For most teams, it’s more than they realise. Mock testing cuts that wait to zero. Instead of calling real services, teams simulate the responses they need. Faster feedback, better isolation, and test runs that don’t fail because a payment sandbox was slow. But like most testing techniques, mocking works well only when used correctly.

While AI accelerates development velocity by a factor of ten, a critical consequence remains: testing hasn’t kept pace. According to SmartBear research, 70% of software professionals report that their application quality has already degraded due to AI-accelerated development. Even more concerning, 60% have experienced quality issues in the past year as development velocity outstrips testing capacity.

Mobile-first businesses often enter the market confident in their app’s speed, but the reality is that many overestimate their performance – and pay for it through user churn and lost revenue. With 5.78 billion unique mobile users worldwide as of October 2025, representing 70.1% of the global population, the pressure to deliver a fast, reliable experience is immense.

Manual testing is essential to quality assurance, but it doesn’t always scale with fast release cycles. Clicking through forms, checking user flows, and repeating the same regression tests before every release can quickly become a bottleneck. Automation testing takes repetitive checks off your QA team’s plate. Instead of manually checking the same flows again and again, teams use testing tools to run predefined tests automatically.

The challenge of any aerospace company is to deliver new capabilities without compromising safety, reliability, or precision. At our current juncture, legacy technology runs into conflict with modern tool stacks. Artificial intelligence (AI) creates fissures in compliance and auditability, and innovation and productivity gains come at a cost of greater complexity. Despite these seismic shifts, the central question remains the same.

Xray has won the Atlassian Marketplace Partner of the Year 2026: Software Collection Apps, recognizing its continued contribution to the Atlassian Marketplace and its role in supporting software teams with native test management inside Jira. The award was announced in Anaheim during Atlassian Team ’26, as part of the Atlassian Marketplace Partner Awards celebrations recognizing outstanding partners across the Atlassian ecosystem.

The first-ever Sembi Software Quality Pulse Report is based on nearly 4,000 responses from QA engineers, developers, security professionals, and engineering leaders worldwide. The findings paint a picture of an industry in motion—and a QA function that increasingly relies on tighter integration, thoughtful AI adoption, and better-connected workflows to keep up. Here's a look at some of the data that matters most for agile QA teams working inside Jira-native environments. TL;DR.

A hospital might have years of EHR data, ICU records, staffing logs, claims history, and diagnostic reports in different systems. Yet it may still miss signs of patient deterioration before an ICU escalation. This gap is why predictive analytics in healthcare has shifted from experimental AI projects to a key strategy in 2026. Now, healthcare organizations use predictive models to identify sepsis risk earlier.