Systems | Development | Analytics | API | Testing

How Developers Organize Web Resources During Software Testing and Development

Modern software development depends on far more than a code editor and source repository. Developers regularly move between documentation, API references, testing tools, staging environments, issue trackers, monitoring dashboards, browser tools, and deployment services. When these resources are scattered across open tabs, messages, bookmarks, and project notes, valuable time is lost simply finding the right page again. A small amount of organization can make both development and testing more efficient.

Ep 90 | Can AI Make Sense of Pharma's Messiest Data?

Human biology is extraordinarily complex, and researchers often have only fragments of information to work with. Brian Martin compares it to looking at a skyscraper through a keyhole: you can see something clearly, but only a tiny piece of the whole. Recorded at EVOLVE26 Singapore, this episode of The AI Forecast brings Paul Muller together with Brian Martin, CTO of Applied AI at Cloudera and co-founder of Rare Hopes NFP, to explore what one of the world’s most data-intensive industries can teach us about AI and decision-making.

Which AI Analyst Holds Up Best for Your Hard Questions?

Analytics vendors claim their AI answers questions accurately, but almost none of them will show you how they checked. The standard move is a percentage with no denominator: "90%+ accuracy on internal benchmarks." No dataset you can download. No scoring method you can inspect. No competitor runs under the same conditions. You're asked to trust the grade without ever seeing the exam1 We ran the exam in public terms instead.

Start your AI agent testing with deterministic tooling

By now everyone is aware of the limitations inherent in generative AI and the AI agents that use it to complete their tasks, and the challenges involved in getting them enterprise quality. If you are planning to incorporate AI agents into your enterprise IT architecture, how are you planning to validate their quality and accuracy?

AI's Impact on Automated Test Script Generation

AI-powered automated test script generation is transforming how software teams approach quality assurance. By analyzing real user behavior, code changes, and system logs, these tools reduce the time and effort needed to create and maintain tests. This shift from manual scripting to AI-generated scripts helps teams keep test coverage in sync with rapid release cycles.

iOS 27 Is Here: How Perfecto Keeps Your Apps Release-Ready

Apple's iOS 27 release marks another significant shift in the mobile landscape. Beyond new features for iPhone users, it signals a familiar pressure point for QA and development teams: the clock starts ticking the moment the update goes live, and your apps need to be ready. Here's why that matters: nearly 80% of iPhone users adopt the newest iOS version almost immediately. That high adoption rate leaves little room for error. If your app breaks on the iOS 27 release, your customers notice fast.