- Review and validate manual test cases for automation needs.
- Maximize daily output by leveraging AI for repetitive coding tasks.
- Regularly use AI to clean up code, improve performance, and update legacy test patterns.
- Prompt AI to analyze bug reports and generate execution summaries.
- Maintain high-quality documentation and READMEs with AI assistance.
- Follow project-specific AI rules to ensure consistency across the automation repository.
- Plan, estimate, and accomplish commitments on time.
- Take part in a code review workflow after using an AI to catch syntax errors, edge cases, and security vulnerabilities.
- Configure and optimize CI pipelines using AI.
- Use LLMs to design BE test cases including edge cases and complex state-transition scenarios.
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