30 Days of AI in Testing Challenge: Day 31 Bonus: Visualise the future of AI in testing
Day 31 bonus reflection visualizing the future of AI in testing, including team roles, workflows, risks, and opportunities for sustainable adoption.
13 min read
Blog
Page 13
30 Days of AI in Testing Challenge: Day 30: Consider what your AI Test Buddy would do for you
Day 30 exploration of what an AI test buddy should do: augmenting planning, generation, analysis, and feedback loops for higher-quality testing.
30 Days of AI in Testing Challenge: Day 29: Share whose work is influencing your AI in testing approach
Day 29 recap of experts and communities influencing my AI-in-testing approach, with key takeaways and how they shape practical testing decisions.
30 Days of AI in Testing Challenge: Day 28: Build your own AI Tools
Day 28 notes on building your own AI testing tools, from problem framing and prototype design to validation and iteration in real workflows.
30 Days of AI in Testing Challenge: Day 27: Assess your team’s readiness to adopt AI-assisted testing
Day 27 reflection on evaluating team readiness for AI-assisted testing, identifying capability gaps, and creating a practical adoption roadmap.
30 Days of AI in Testing Challenge: Day 26: Investigate strategies to minimise the carbon footprint of AI in testing
Review articles on AI energy use and carbon emissions, then consider sustainability across model training, data centers, storage, and testing.
30 Days of AI in Testing Challenge: Day 25: Explore AI-driven security testing and share potential use cases
Explore AI-driven security testing through research, weighing team barriers, potential benefits, and risks when deciding where such tools fit.
30 Days of AI in Testing Challenge: Day 24: Investigate code explanation techniques and share your insights
Use ChatGPT-4 to explain JavaScript bubble and selection sort, then assess usefulness for testers and derive test ideas from the explanations.
30 Days of AI in Testing Challenge: Day 23: Assess AI effectiveness in visual testing and discuss the advantages
Trial Percy for visual testing by comparing snapshots after page-layout and small-icon changes, then review detection results and risks.
30 Days of AI in Testing Challenge: Day 22: Reflect on what skills a team needs to succeed with AI-assisted testing
Explore the skills and roles needed for AI-assisted testing teams, including an AI ethics expert and a training and development manager.
30 Days of AI in Testing Challenge: Day 21: Develop your AI in testing manifesto
Review lessons from the AI testing challenge and draft a personal manifesto with principles for working with AI in testing.
30 Days of AI in Testing Challenge: Day 20: Learn about AI self-healing tests and evaluate how effective they are
Test Katalon Studio's self-healing feature by changing WebUI locators and step order, then assess recovery behavior and possible failure cases.