Spec-driven development is quietly changing how embedded engineers work with AI coding agents. If you have handed a coding agent a prompt, you know the failure mode. The code compiles. It looks right.

Solve the biggest challenges in your codebase. Unifying system insights for smarter, faster debugging Engineering leaders today face a growing paradox: ship software faster while reducing defects, all ...

Nahda Nabiilah is a writer and editor from Indonesia. She has always loved writing and playing games, so one day she decided to combine the two. Most of the time, writing gaming guides is a blast for ...

Goodfire wants to make training AI models more like good old-fashioned software engineering. The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and ...

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Cursor AI Coding is reshaping how developers build software by combining a GPT-powered IDE with intelligent automation. Instead of switching between tools, developers can rely on a single AI coding ...

As AI agents transition from simple chatbots to autonomous systems capable of managing cloud incidents, navigating complex web interfaces, and executing multi-step API workflows, a new challenge has ...

If you are interested in learning more about the new Claude Code Superpowers plugin and its ability to enhance AI-driven software development by embedding disciplined practices into the coding process ...

In biotech today, AI is no longer new. Predicting molecular structures, finding drug candidates, filtering toxicity early—these innovations are often summarized in one sentence: AI makes drug ...

Large language model (LLM)-based multi-agent systems are challenging to debug because failures often arise from long, branching interaction traces. The prevailing practice is to leverage LLMs for ...

Java is becoming more popular for building AI applications, with 62% of respondents in Azul’s just-released 2026 State of Java Survey and Report relying on Java for AI development. Last year’s report ...