AI Testing Made Trustworthy using FizzBee Podcast Por capa

AI Testing Made Trustworthy using FizzBee

AI Testing Made Trustworthy using FizzBee

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 As AI tools like Copilot, Claude, and Cursor start writing more of our code, the biggest challenge isn't generating software — it's trusting it. In this episode, JP (Jayaprabhakar) Kadarkarai, founder of FizzBee, joins Joe Colantonio to explore how autonomous, model-based testing can validate AI-generated software automatically and help teams ship with confidence. FizzBee uses a unique approach that connects design, code, and behavior into one continuous feedback loop — automatically testing for concurrency issues and validating that your implementation matches your intent. You'll discover: Why AI-generated code can't be trusted without validation How model-based testing works and why it's crucial for AI-driven development The difference between example-based and property-based testing How FizzBee detects concurrency bugs without intrusive tracing Why autonomous testing is becoming mandatory for the AI era Whether you're a software tester, DevOps engineer, or automation architect, this conversation will change how you think about testing in the age of AI-generated code.
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