Worked on the openshift-pipelines/pipelines-as-code repository to expand AI analysis capabilities across all completed PipelineRuns, enabling insights from both successful and failed executions. Updated the analyzer logic in Go to support this broader scope and implemented a fix ensuring default AI roles run on every completed PipelineRun. The approach included rigorous test-driven development, with new tests verifying the updated behavior and Markdown documentation clearly communicating the changes. This work enhanced observability and actionable insights within the pipeline system, demonstrating skills in AI integration, Go development, and testing, while contributing maintainable code and comprehensive documentation to the project’s codebase.