AI code created a new testing problem | From the Bear Cave Ep. 3

SmartBear’s study Closing the AI software quality gap found that 60% of teams have already experienced quality issues tied to AI-generated code, evidence of how increased abstraction is changing how software gets built. When development shifts from well-defined requirements to prompts and generated outputs, it becomes much harder to understand what the system is actually supposed to do, and what you should be testing against.

In this From the Bear Cave clip, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel explore a less obvious challenge with AI-generated code: the loss of clear intent and the impact of increased abstraction.

They also introduce the concept of application integrity – continuous, measurable validation that software behaves as intended – and what that means in practice for teams trying to keep up with AI-driven development.
Ready to do quality at AI speed and scale? See how BearQ’s always-on AI teammates autonomously explore, test, and validate your applications so you can ship faster with confidence: https://smartbear.com/product/bearq/