Before asking whether an agent hallucinated, misunderstood a request or made a bad decision, ask: did the work run at all?

AI engineering builds on established software engineering principles, but it also introduces a host of new challenges.

The teams winning with AI agents right now share one trait: they stopped treating security at the end of the pipeline, but as ...

For example, our own research of 820 IT professionals worldwide found that while 77% have confidence in AI outputs, only 39% ...

The new SnapGPT evolves from an AI-powered integration copilot into an agentic assistant for the integration life cycle.

Veracode’s 2026 GenAI Code Security Report finds AI-generated code security has stalled at a 56 percent pass rate — with ...

Cobalt's Autonomous Pentest combines AI orchestration and 500 vetted human testers to deliver penetration testing findings in ...

Nissy works in two key ways: checking your intent before code is created, and checking all the actions the agent carried out.

Tabnine’s Enterprise Context Engine gives AI quality and testing agents system-level understanding of enterprise software environments, making agentic AI accurate, safe, and effective across complex ...

Harness, the AI Software Delivery Platform company, today announced it is extending its platform to cover the full AI Agent ...

Engineering leaders have always known the cost of maintaining and securing dead or unused code is expensive. What’s changed is who pays the bill.