Awesome QA Prompt: Using AI to Make Testing Work Better
Awesome QA Prompt an AI prompt library for QA work. The idea is to capture expert testing knowledge in prompt templates, so AI can work like a senior test engineer
Focused on QA, AI, testing engineering, and terminology, with fast entry points to bilingual posts, AI Wiki, QA Wiki, and hands-on projects.

Testing Types
Testing Workflows
A curated AI prompt collection for QA and software testing, covering the full testing lifecycle with 15+ test types, 3 workflows, and 225+ documents. Bilingual (EN/CN), supports ROSES, LangGPT, ICIO, CRISPE, RISE frameworks.
A Chinese version of QA and software testing glossary wiki for personal learning. Covers terms from A/B Testing, Acceptance Testing, API Testing, to Agile Testing and more.
API test starter using Bruno (open source, MIT). Supports Postman/Insomnia collection import, Assert & Tests scripts, environment variables, and CI/CD integration (e.g. GitHub Actions).
API test starter with RestAssured for Java. Structured project for REST API automation with Maven and JUnit.
Systematic test automation learning paths, from beginner to advanced
Awesome QA Prompt an AI prompt library for QA work. The idea is to capture expert testing knowledge in prompt templates, so AI can work like a senior test engineer
Day 31 bonus reflection visualizing the future of AI in testing, including team roles, workflows, risks, and opportunities for sustainable adoption.
Day 30 exploration of what an AI test buddy should do: augmenting planning, generation, analysis, and feedback loops for higher-quality testing.
Day 29 recap of experts and communities influencing my AI-in-testing approach, with key takeaways and how they shape practical testing decisions.
Day 28 notes on building your own AI testing tools, from problem framing and prototype design to validation and iteration in real workflows.
Day 27 reflection on evaluating team readiness for AI-assisted testing, identifying capability gaps, and creating a practical adoption roadmap.
Selected AI and vibe-coding terms across models, agents, context, rules, and engineering practices.