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Really insightful breakdown of how AI is shaping continuous testing. The shift from reactive to predictive quality is exactly where the industry is heading.

I’m particularly interested in your perspective on the 'human-in-the-loop' aspect. Even with advanced AI models, many organizations I work with still struggle with the initial setup and maintenance of flaky pipelines. In your view, has AI maturity reached a point where it’s largely 'hands-off' for continuous testing services, or do you still see a high need for manual intervention to ensure data integrity?