The Obvious, the Obscured, and the Illusion: Navigating the Noise of GenAI in Testing
About Topic
In a world brimming with innovations and solutions, the journey to using GenAI in testing is often shadowed by a paradox: the obvious truths become hidden behind layers of noise, and illusions arise in their place. Rahul peels back the layers that veil judgment. This talk explores the essence of problem-solving, questioning whether the challenges we face have already been resolved by existing tools or if they demand the unique touch of new technology. Why do we reach for GenAI, and what does it promise to solve that others cannot? And ultimately, can the old and new coexist, each serving its rightful purpose, without clouding our vision?
Rahul unravels these questions and more, guiding you through the path where clarity unfolds itself. Through a real-world case study, he will illustrate how GenAI can be leveraged meaningfully, emphasizing how understanding and restraint are key to sifting through the noise and seeing the obvious with renewed eyes. This keynote is a call to embrace both simplicity and innovation, to cut through the illusions, and to navigate the path where GenAI is not just noise, but a genuine part of the testing story.
Key Takeaways
1. Innovation creates noise, making obvious truths harder to see.
2. Question if a problem really needs GenAI or if existing tools suffice.
3. Understand GenAI’s true value beyond the hype.
4. Old and new solutions should complement, not replace, each other.
5. A real-world case study shows how GenAI can be used effectively.
6. Clarity comes from cutting through illusions and embracing simplicity.
About Speaker
Rahul Verma is an awarded thought leader for his contributions to the testing community. He is a Senior Coach and Consultant with trendig technology services gmbh. He is the creator of Swayam – an LLM framework for layered prompting and Arjuna – a free, open-source Python based modern test automation framework. He is a contributing author and reviewer for various certification bodies including Artificial Intelligence United, Selenium United, ISTQB and CMAP.
His software testing experience includes using Large Language Models in testing, building test automation frameworks in Python, web security, white box testing and web performance testing. His research work focuses on exploring meta-programming and object oriented design patterns as applied to automating activities in all these areas.
He has presented, published articles and educated thousands of testers in the said areas. His testing ideas and work are deeply influenced by his deep interest in poetry and spirituality.
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