Cloud Native Testing Podcast
The Cloud Native Testing Podcast, sponsored by Testkube, brings you insights from engineers navigating testing in cloud-native environments.
Hosted by Ole Lensmar, it explores test automation, CI/CD, Kubernetes, shifting left, scaling right, and reliability at scale through conversations with testing and cloud native experts.
Learn more about Testkube at http://testkube.io
Cloud Native Testing Podcast
QA Is Dead: Trust, Spec Recovery, and Autonomous Testing with JDAQA’s Jay Aigner
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In this episode of the Cloud Native Testing Podcast, host Ole Lensmar sits down with Jay Aigner, CEO of software quality assurance firm JDAQA, to unpack the "QA is dead" debate. Picking up the conversation from their roundtable in Philadelphia, Jay explains why he believes QA has always been broken: a safety net bolted onto the end of the pipeline worked for decades, but at the speed code ships today, quality has to be understood across product, engineering and validation.
Ole shares what he saw at LeadDev New York and StarWEST, where teams are building AI into their quality pipelines with surprisingly little pushback. Together they dig into the hardest open question in autonomous testing: how do you trust the tests an AI writes for you? Jay makes the case for maximizing what AI can cover while keeping humans where judgment matters, explains how JDAQA uses AI for spec recovery, and weighs in on whether AI will make the choice of testing tool irrelevant.
Key Topics Discussed:
- Why "QA Is Dead": Why QA can no longer be bolted onto the end of the pipeline, and why the quality of what goes into the machine now shapes the end result more than ever.
- The Trust Problem in Autonomous Testing: Verification as the new bottleneck, whether AI can be trusted to guardrail itself, and why mission-critical software still needs a higher bar.
- Balancing AI and Human Judgment: Maximizing the surface area AI can cover while retaining humans for judgment, and why realistic velocity gains beat 10X hype.
- The Three SDLC Buckets: Traditional, AI-enabled and agentic SDLCs, why teams are turning to assessments to find where they stand, and the rise of roles like the quality systems architect.
- Spec Recovery and the Living Spec: Using AI to rebuild stale product documentation, validating it with stakeholders, and turning it into a version-controlled spec that AI guardrails are built on.
- Do Testing Tools Still Matter? Whether AI will abstract away the choice between Playwright, Cypress and other frameworks, and how JDAQA pairs AI-written Playwright tests with human review.
