The Boston startup uses AI to translate and verify legacy software for defense contractors, arguing modernization can’t come at the cost of new bugs.

AI can speed up testing, but if you trust it too much, you might ship bugs faster than ever — with no one clearly accountable.

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

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

Imagine waking up to find that while you slept, a complex feature for your app was not only coded but also tested and debugged, all without your direct involvement. This isn’t a scene from a sci-fi ...

The 13th annual report reveals a 24% income gap between strategic leaders and ICs, while new data shows hands-on AI ...

Combine AI-generated tests with intelligent test selection to manage large regression suites and speed up feedback ...

Allocating capital to autonomous security platforms outperforms traditional consultant-driven validation models.

I spent three weeks testing no-code AI app builders after watching demos that promised perfect apps from single sentences.

Quality engineering must evolve faster than code; otherwise, agentic AI will move quickly, learn rapidly and fail expensively.

The biggest bottleneck for engineering leaders isn’t writing code, but waiting for validation — especially across time zones. AI eliminates this bottleneck by testing code the moment it’s written, ...