The Power of Human and AI Collaboration in Software Testing
summary
Claims that almost 60% of QA still avoid AI and that delegating routine work doubles QA throughput and makes automation about four times faster. Delivers runnable artifacts: generated Kotlin + Selenium UI tests following page‑object and package structure, test data classes using Faker, API test examples from Swagger and REST‑assured, auto‑written bug reports that find contradictory acceptance criteria, and a small CV‑improvement product driven by GPT‑4 with an accompanying repository.
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chapters (12)
- 0:00Introduction
- 1:31AI usage in QA survey
- 2:56Human-AI collaboration theory
- 5:11AI terms and models
- 6:58Crafting AI prompts
- 13:33AI applications in QA
- 20:27Manual QA tasks delegation
- 25:10AI test case generation
- 30:56AI for QA leadership
- 35:38AI in career development
- 39:59AI productivity impact
- 41:07Conclusion
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