The recently observed phenomenon of ‘doomprompting’ with LLM and AI agent results can lead to poor outcomes and huge costs.

AI is increasing both the number of pull requests and the volume of code within them, creating bottlenecks in code review, integration, and testing. Here’s how to address them.

Over the summer, the University of Mary Washington in Virginia offered all students a one-credit online course on how to use ...

Learn how to optimize your ChatGPT-5 prompts and interactions with weirdly effective tips for smarter, more tailored responses. Powerful ...

Pair programming with ChatGPT Codex for a week exposed hard-won lessons every developer should know before trying it.

AI is becoming an active participant in the software development lifecycle, helping teams deliver quality output at pace and ...

More Kenyans are turning to AI tools like Gemini and ChatGPT for quick, affordable financial advice once reserved for costly ...

AI can, in theory, make people more productive. But the results of a recent study show this is not guaranteed, as people ...

With Magistral 1.2, Mistral continues its dual-path strategy: delivering open, efficient models for developers, while scaling enterprise-ready tools with measurable advantages in reasoning, ...

Statistical testing in Python offers a way to make sure your data is meaningful. It only takes a second to validate your data ...

Cool demos aren’t enough — your team needs ML chops and context skills to actually get AI agents into production.

It’s beneficial for those who want to preserve media they can’t easily replace, and it gives you full control without a ...