GitHub Copilot testing for .NET in Visual Studio 2026 v18.3 can generate tests for the xUnit, NUnit, and MSTest test ...

Engineering teams can’t afford to treat AI as a hands-off solution; instead, they must learn how to balance experimentation ...

Struggling to debug your physics simulations in Python? This video uncovers common mistakes that cause errors in physics code and shows how to identify and fix them efficiently. Perfect for students, ...

As companies move to more AI code writing, humans may not have the necessary skills to validate and debug the AI-written code if their skill formation was inhibited by using AI in the first place, ...

Many teams are approaching agentic AI with a mixture of interest and unease. Senior leaders see clear potential for efficiency and scale. Builders see an opportunity to remove friction from repetitive ...

Python -O won’t magically make every script faster, but in the right workloads it’s a free win—here’s how to test it safely.

As some of the world’s largest tech firms look to AI to write code, new research shows that relying too much on AI can impede ...

Does vibe coding risk destroying the Open Source ecosystem? According to a pre-print paper by a number of high-profile ...

Google’s ATLAS study reveals how languages help each other in AI training, offering scaling laws and pairing insights for better multilingual models.

In some ways, data and its quality can seem strange to people used to assessing the quality of software. There’s often no observable behaviour to check and little in the way of structure to help you ...

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...