Worked on UI quality improvements for the microsoft/magentic-ui repository, focusing on enhancing the AI model configuration experience. Addressed a critical issue by correcting the Azure Endpoint label to display as 'Azure API Key' and refining error messaging for the Base URL field, which improved clarity and reduced the risk of misconfiguration during AI model setup. Leveraged frontend development skills with React, JavaScript, and TypeScript to implement concise, ticket-aligned changes that minimized regression risk. The updates supported smoother onboarding and lowered support friction for AI deployments, demonstrating a methodical approach to targeted UI corrections within a complex configuration workflow.