How do you reduce test automation maintenance?

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This week’s article, “Creating self-healing automated tests with AI and Playwright” by @sshray, details how combining AI language models with Playwright can significantly reduce the time spent on test automation maintenance.

What You’ll Learn:

:robot: AI-powered test automation: Discover how AI language models like Groq, Llama, and Mistral assist in generating self-healing test scripts, reducing manual intervention and maintenance.

:hammer_and_wrench: Self-healing tests: Learn how the integration of AI can fix failing tests automatically by adjusting to changes in the application, minimizing the need for constant test updates.

:zap: Optimising efficiency: Explore how this setup can improve efficiency by automating error detection, code suggestions, and script updates.

After reading, we’d love to hear from you:

Have you tried integrating AI into your test automation workflows? Share your experiences or challenges with self-healing tests

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Isn’t using an AI losing control of what you’re testing, how, and why?
How is the risk managed when giving AI the power over a good piece of automation code?
Is the AI responsible for the automation or the tester?
Using the self-healed code, is the automation engineer experienced enough in those software development concepts to manage that going further?

The author seems to create an equivalence between testing = automated checks = AI (which can repair my crappy automation)

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