AI-powered testing tools are exploding across software engineering teams… but so are the hidden costs.

In this episode, Joe sits down with Arthur Hicken to unpack the growing problem of runaway AI token usage, unexpected LLM billing, and the operational risks of deploying AI agents into testing and DevOps pipelines. Inspired by Arthur's article on the emerging "Token Tax," this conversation explores why many teams are underestimating the true cost of AI automation.

You'll learn:

Why AI-generated testing can create unexpected scaling costs
How runaway AI agents and infinite loops happen
Real-world examples of massive AI billing surprises
Why deterministic problems shouldn't always use LLMs
The hidden risks of "vibe testing" and autonomous AI remediation
How QA teams can monitor, test, and control token usage
Why performance testing and service virtualization matter more than ever in AI systems
Practical strategies to avoid expensive AI deployment mistakes

Whether you're a software tester, automation engineer, QA leader, or DevOps practitioner, this episode will help you think more strategically about AI testing before costs spiral out of control.