Case studies from a year of integrating AI into real testing workflows
How can AI tools transform time-consuming testing tasks without sacrificing quality? My journey from skeptic to advocate shows that strategic AI implementation provides practical solutions for everyday QA challenges.
In this session, I'll share how implementing AI tools in specific testing areas became a competitive advantage, resulting in faster test creation, improved coverage, and more efficient documentation.
Timeline:
- Introduction: The current state of AI in testing - separating hype from reality
- Framework Overview: Three areas where AI delivers immediate testing value
- Case Study: How I used ChatGPT and Claude to generate test scenarios for a homepage video component in 5 minutes instead of an hour - I'll show you the exact prompts that worked for me
- Decision Tools: My top prompts for test design planning that helped me analyze requirements and generate scenarios faster
- Implementation Tips: What I've found works best - starting small, documenting what works, and gradually expanding
Attendees will leave with practical resources: the collection of prompts I use, my 15-minute review workflow that ensures quality, and my approach to implementing AI for both test case generation and debugging support.
This presentation is designed for QA professionals facing the "fast and cheap" challenge I've experienced, looking for ways to meet tight deadlines without cutting corners on quality.
