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Episode 14: AI-Powered Testing Practices with Alex Martins

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Manage episode 404949743 series 3461985
Content provided by Curiosity Software. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Curiosity Software or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Welcome to episode 14 of Inside The Outer Loop! In this episode, the Curiosity Software team, Rich Jordan and Ben Johnson-Ward, are joined by Alex Martins, VP of Strategy at Katalon, to discuss the implications and challenges of AI-Powered Testing. This episode goes beyond the hype and marketing euphoria of AI, to weigh up productivity gains coming from GPT-4 and large language models (LLM) in the software quality space. Guest Alex Martins leads the conversation around the need to put the tester at the centre of AI-powered testing, and only then, start building out AI use cases and safeguards. Where the development community has seen tangible gains in AI deployment, the uplift in AI-powered testing practices is just beginning. So, how will this impact software testing professionals? Also, how will SME knowledge evolve as organizations develop bespoke LLMs? Ben Johnson-Ward argues, if artificial intelligence is used to create test outputs, then testers will have to evaluate the output of these tests to determine if they are correct. This approach may lead to a decrease in productivity as testers spend time testing the output of AI generated tests. Testers will be able to fine-tune their AI models and build out a broader toolkit. But what does this look like? While organizations are adopting AI in testing, there will also be impact on the metrics of repeatability, explainability, and auditability. With this in mind, internal AI committees can establish rules to abate uncertainty. Rich Jordan follows up on Ben's point, explaining how from the human perspective, AI may be limited in determining if an application meets the needs of the users. In this use case, AI becomes the co-pilot, a new tool for experts to enhance collaboration, while testers remain primary-pilots. Repeatability is discussed as a characteristic that humans are comfortable with in testing, but can AI offer better alternatives to traditional methods of monitoring code changes and integration flows? AI-powered practices in software testing and test coverage are still in their early stages. This requires ongoing collaboration, learning, and sharing of experiences among organizations and industry professionals. Finally, the possibilities and potential benefits of AI are too significant to ignore, despite the discomfort and challenges it brings in delivering quality software, faster. Inside the outer loop – brought to you by the Curiosity Software team! Together with industry leaders and experts, we uncover actionable strategies to navigate the outer loop of software delivery, streamline test data management, and elevate software quality. Tune in to transform the way you think about software delivery, quality, and productivity!
  continue reading

34 episodes

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Manage episode 404949743 series 3461985
Content provided by Curiosity Software. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Curiosity Software or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Welcome to episode 14 of Inside The Outer Loop! In this episode, the Curiosity Software team, Rich Jordan and Ben Johnson-Ward, are joined by Alex Martins, VP of Strategy at Katalon, to discuss the implications and challenges of AI-Powered Testing. This episode goes beyond the hype and marketing euphoria of AI, to weigh up productivity gains coming from GPT-4 and large language models (LLM) in the software quality space. Guest Alex Martins leads the conversation around the need to put the tester at the centre of AI-powered testing, and only then, start building out AI use cases and safeguards. Where the development community has seen tangible gains in AI deployment, the uplift in AI-powered testing practices is just beginning. So, how will this impact software testing professionals? Also, how will SME knowledge evolve as organizations develop bespoke LLMs? Ben Johnson-Ward argues, if artificial intelligence is used to create test outputs, then testers will have to evaluate the output of these tests to determine if they are correct. This approach may lead to a decrease in productivity as testers spend time testing the output of AI generated tests. Testers will be able to fine-tune their AI models and build out a broader toolkit. But what does this look like? While organizations are adopting AI in testing, there will also be impact on the metrics of repeatability, explainability, and auditability. With this in mind, internal AI committees can establish rules to abate uncertainty. Rich Jordan follows up on Ben's point, explaining how from the human perspective, AI may be limited in determining if an application meets the needs of the users. In this use case, AI becomes the co-pilot, a new tool for experts to enhance collaboration, while testers remain primary-pilots. Repeatability is discussed as a characteristic that humans are comfortable with in testing, but can AI offer better alternatives to traditional methods of monitoring code changes and integration flows? AI-powered practices in software testing and test coverage are still in their early stages. This requires ongoing collaboration, learning, and sharing of experiences among organizations and industry professionals. Finally, the possibilities and potential benefits of AI are too significant to ignore, despite the discomfort and challenges it brings in delivering quality software, faster. Inside the outer loop – brought to you by the Curiosity Software team! Together with industry leaders and experts, we uncover actionable strategies to navigate the outer loop of software delivery, streamline test data management, and elevate software quality. Tune in to transform the way you think about software delivery, quality, and productivity!
  continue reading

34 episodes

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