Manual QA is inefficient for scaling. As test coverage grows, so does the need for additional resources. Test cycles become longer, with higher risks of human error. This directly impacts release timelines, often leading to delays or incomplete testing. On the other hand, no-code QA tools promise fast deployment and ease of use, but often fail to provide flexibility for complex testing scenarios. They may create technical debt, requiring frequent upkeep and engineering intervention, especially when handling real-world testing complexities like API integrations or asynchronous behaviors.