AI Testing LLMs & RAG: What Testers Must Validate with Imran Ali
with Imran Ali
founder
About this episode
AI is transforming how software is built, but testing AI systems requires an entirely new mindset.
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In this episode, Joe Colantonio sits down with Imran Ali to break down what AI testing really looks like when you’re dealing with LLMs, RAG pipelines, and autonomous QA workflows.
Why traditional pass/fail testing breaks down with LLMs
How to test non-deterministic AI outputs for consistency and accuracy
Practical techniques for detecting hallucinations, grounding issues, and prompt injection risks
How RAG systems change the way testers validate AI-powered applications
Where AI delivers quick wins today—and where human validation still matters
This conversation goes beyond hype and gets into real-world AI testing strategies QA teams are using right now to keep up with AI-generated code, faster release cycles, and DevOps velocity.
If you’re a tester, automation engineer, or QA leader wondering how AI changes your role, not replaces it, this episode is your roadmap.
Over 2 decades in QA, A lot of that time as a test automation expert, developing frameworks and solutions for automation and API testing using cutting-edge tools.
I was also the founder of Tricky Defects, where I've previously delivered Selenium and BDD courses and workshops both online and in person.
My work these days focuses on leading AI Test Group, helping teams adopt AI-powered QA and testing at scale using our AI Test Platform. We are also addressing the unique testing challenges of generative AI, from RAG pipeline validation to LLM output evaluation, and building the tooling and frameworks needed to bring rigorous quality assurance practices to non-deterministic AI systems.
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