AI Testing Made Trustworthy using FizzBee

Failed to add items

Sorry, we are unable to add the item because your shopping cart is already at capacity.

Add to basket failed.

Please try again later

Add to Wish List failed.

Please try again later

Remove from Wish List failed.

Please try again later

Follow podcast failed

Unfollow podcast failed

AI Testing Made Trustworthy using FizzBee

Listen for free

View show details

About this listen

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.

No reviews yet