Why Most AI QA Strategies Fail Before Testing Even Starts
A lot of teams think their AI quality problem begins when the first test run starts but it usually begins much earlier.
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Modern Software Development For Today's Systems & Applications
The latest News and Information on Software Testing and related technologies.
Your Guide to Perforce Autonomous Testing
Software testing is struggling to keep pace with modern release cycles. More code, faster deployments, fragmented tools, and increasing quality demands are creating bottlenecks for QA, engineering, and DevOps teams. Discover how Perforce Autonomous Testing transforms the way teams validate software by bringing functional, performance, web, mobile, and desktop testing together through a unified AI-driven experience. Using natural language, teams can define testing intent, automate execution, orchestrate complex workflows, and gain actionable insights faster than ever before.
How to Test AI Applications Manually: A Playbook for Hallucinations, Bias, and Non-Deterministic Outputs
You have tested hundreds of features. You know the drill. Open the test case, write the preconditions, list the steps, fill in the expected result, run it, compare. Pass or fail. Move on. Then someone hands you an AI feature. A chatbot. A "summarize this ticket" button. A search box that answers in full sentences instead of returning a list of links. You open your test case template, you get to the "expected result" field, and you stop.
The 2026 State of Neobanking: Market Size, Profitability Trends, and Tech Stack Shifts
The state of neobanking 2026 looks very different now. A few years ago, most digital banks were chasing growth at any cost. More users. More app downloads. More market buzz. Today, the focus has shifted. Investors want profitable business models. Regulators want tighter compliance. Customers expect their neobank to feel as reliable as a traditional bank, but far more seamless to use. The industry is finally moving from hype toward operational maturity.
Will AI Replace Manual Testers? Katalon's Data Says the Story Is More Complicated
If you only follow the loudest headlines, it is easy to believe AI is about to wipe out manual testing. Katalon's State of Software Quality Report 2025 tells a more useful story, and it comes from inside the industry: over 1,500 QA professionals, from individual contributors to senior executives, across North America, Europe, and Asia-Pacific.
Enterprise test management: Should you build or buy in the age of AI?
AI has opened the door for teams to build tools they previously had to buy. With the right prompts and internal workflows, teams can generate test cases, summarize results, analyze defects, and automate parts of the testing process faster than ever. For enterprise QA and engineering leaders, that raises a practical question: “should we build our own test management layer, or adopt an AI-powered test management platform?” It’s a fair conversation to have.
Why Fable 5 is an Existential Crisis
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News Analysis 2026: How AI Performance Testing Tools Are Transforming Software Quality
This summer, leading performance testing platforms have introduced a new wave of AI capabilities that are fundamentally changing how software teams validate application speed and reliability. Rather than incremental updates, these advances mark a step change: AI performance testing now enables faster test creation, greater accuracy, and wider accessibility across teams.
How Xray's AI Test Prioritization Helps Teams Focus on High-Risk Tests
Test execution is one of the most time-sensitive stages of software delivery. Teams are expected to validate functionality, ensure stability, and support release decisions within increasingly shorter development cycles. Even with strong automation in place, there is rarely enough time to execute every Test before a release. This makes prioritization a critical part of the QA process.
How To Reduce Test Maintenance Without Losing Coverage
If your team spends more hours fixing tests than writing features, you already know the problem. You don’t need another lecture on "why testing matters." You need to reduce test maintenance without gutting your coverage, and you need it to actually stick past next sprint.