AI will kill flaky UI scripts, and “click-and-verify” roles. That’s overdue. What won’t disappear is the need to understand how systems actually behave under stress, failure, and ambiguity.
The future of QA is upstream:
• defining invariants, not writing scenarios
• modeling state and failure modes, not chasing bugs
• debugging distributed, async, messy real-world systems
AI will generate tests faster than humans ever can. But it won’t know what matters or what assumption is wrong. That judgment still belongs to engineers.
If you’re in QA and want to stay relevant: stop being a test executor. Become the person who explains why the system broke, not just how to reproduce it.
AI will kill flaky UI scripts, and “click-and-verify” roles. That’s overdue. What won’t disappear is the need to understand how systems actually behave under stress, failure, and ambiguity.
The future of QA is upstream: • defining invariants, not writing scenarios • modeling state and failure modes, not chasing bugs • debugging distributed, async, messy real-world systems
AI will generate tests faster than humans ever can. But it won’t know what matters or what assumption is wrong. That judgment still belongs to engineers.
If you’re in QA and want to stay relevant: stop being a test executor. Become the person who explains why the system broke, not just how to reproduce it.