Zulfaqar Azmi contributed to the tier4/autoware_launch repository by enhancing diagnostics and system configuration for autonomous vehicle software. In March 2025, Zulfaqar streamlined the diagnostics subsystem by removing unused trajectory deviation reporting, reducing maintenance overhead and simplifying issue triage. Later, in August, Zulfaqar implemented boundary departure diagnostics within the planning system, integrating observability and error reporting with the Motion Reference Model. These updates involved targeted YAML configuration changes and leveraged expertise in Autoware and system configuration. Zulfaqar’s work focused on improving diagnostic clarity and proactive error detection, demonstrating a methodical approach to maintainability and system-level monitoring in production environments.