Join Jason Arbon, CEO of Checkie.AI, to explore how integrating AI into your testing strategy can accelerate your career and drive success. Learn how to leverage AI to enhance testing efficiency and avoid common pitfalls that can hinder career advancement. Discover practical strategies for using AI to improve your testing processes and gain visibility in your field.
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What are the key indicators that an AI tool is enhancing your testing efficiency and supporting your career growth?
Jason Arbon: The key indicators that an AI tool is enhancing your testing efficiency include reduced time to execute tests, increased test coverage, and the ability to identify complex patterns or issues that might have been missed with traditional testing methods. For career growth, an AI tool should also enable you to develop new skills, adapt to evolving testing methodologies, and position yourself as a more valuable asset in your organization by staying ahead of industry trends.
Don’t you think any kind of testing (even asking silly questions) is good for exploring what are the limitation of an LLM?
Jason Arbon: Absolutely, any kind of testing, including asking what might seem like silly questions, is valuable for exploring the limitations of a Large Language Model (LLM). These tests can uncover unexpected behaviors, edge cases, and gaps in the model’s understanding. The more diverse the testing, the better we can understand the strengths and weaknesses of the LLM.
What do you think that in future we will have a label that “it was tested by AI” similar to “generated by AI”? Human work will be more expensive and business can choose something in the middle?
Jason Arbon: It’s quite possible that in the future we could see labels indicating that something was “tested by AI,” similar to “generated by AI.” As AI continues to evolve and take on more testing responsibilities, human work, especially in complex or nuanced scenarios, may become more specialized and therefore more expensive. Businesses might opt for a hybrid approach, leveraging AI for efficiency while relying on human expertise for critical or creative tasks.
What strategies should testers use to effectively promote their AI testing skills to potential employers?
Jason Arbon: To effectively promote AI testing skills to potential employers, testers should highlight specific examples where AI tools have significantly improved testing outcomes, such as detecting issues faster or increasing test coverage. Demonstrating a deep understanding of AI tools, staying updated on the latest trends, and showcasing certifications or courses in AI and machine learning can also make you more attractive to employers. Additionally, being able to articulate how AI skills have contributed to overall business goals and quality improvements will further enhance your appeal.
