Nandini Srinivasan has spent 25 years in the quality industry and leads a global QA organization of over 150 engineers across the US, Canada, India, and Pakistan.
In this episode, she breaks down exactly how she built a QA AI acceleration charter, ran a train-the-trainer model, and used a phased proof-of-concept approach to separate real AI from what she calls "powerful automation dressed up as AI.
We get into:
How she frames quality metrics for executives
Using language around revenue protection
Risk mitigation
Feature velocity instead of test coverage percentages.
She talks about the four pillars she uses to present her team's value: quality, scalability, performance, and availability.
Nandini also shares her take on the future of QA hiring, why the judgment layer will always require a human, and what skills testers need to stay relevant as AI agents take over the more mechanical parts of automation.
She is also writing a five-part LinkedIn series called "The Voice of QA in the AI Era" if you want to follow along.
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