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The latest News and Information on Software Testing and related technologies.

AI in Credit Underwriting: Improving Risk Assessment Accuracy

For years, credit underwriting was pretty straightforward. Lenders looked at a few fixed factors like credit scores and income, to decide who was worthy of a loan. If you didn’t fit the criteria, you were simply rejected. It worked, but only to a point. This approach left out many people who were actually creditworthy and often missed subtle shifts in market stability.

Flaky Tests in Test Automation: How AI Is Finally Solving the Problem

You push a commit. The pipeline goes red. You run it again and get green. No code changed. Nothing in the environment changed. And yet, the result is different. If that sounds familiar, you're not alone. Flaky tests in test automation are one of the biggest hidden productivity drains in modern software delivery, and most teams are still treating them as a minor annoyance rather than a systemic problem. Spoiler: they're not minor. And the way teams traditionally try to fix flaky tests? It mostly backfires.

Top Challenges Hospitals Face Without a Centralized HMS - And How to Solve Them (2026)

Most hospitals are digitally enabled, but not digitally connected. Patient information exists across registration systems, EHRs, lab software, pharmacy tools, and billing platforms. Each system captures data, but none owns the full patient journey. Staff move between screens, re-enter information, and rely on manual coordination to keep workflows moving. This is the underlying reality behind the challenges hospitals face without a centralized HMS.
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Run Local LLMs on Mac to Cut Claude Costs

Part of the motivation for this post is how cloud API economics are shifting: Anthropic is moving large enterprise customers toward per-token, usage-based billing (unbundled from flat seat fees), which makes "always call the API" a moving cost line for teams at scale. A hybrid or local layer is one way to keep spend bounded while you still use premium models where they matter.

Scale AI test automation without losing visibility | QMetry + Reflect integration

AI is changing how testing gets done. As automation grows, so does the complexity of tracking what’s been tested, what passed, and what’s ready to release. See how SmartBear Reflect and QMetry work together to scale AI-powered test automation without losing visibility or control. Reflect makes it easy to create and run automated tests using plain language, while QMetry brings structure to that speed, connecting tests, results, and reporting into a single system of record.

News Analysis 2026: How Serverless Architecture Is Transforming Performance Testing

In just a few years, serverless architecture has moved from an emerging trend to a core pillar of enterprise IT. By 2026, platforms like AWS Lambda, Azure Functions, and Google Cloud Functions are handling production workloads at scale for organizations worldwide. The draw is clear: instant scalability, no server management, and a usage-based billing model that can lower costs for unpredictable workloads.