Worked on the ai-dynamo/dynamo repository with a focus on backend reliability and validation correctness. Addressed a critical issue in the planner configuration path by fixing a typo in the PlannerConfig.decode_scale_up_kv_rate validation alias, which previously risked incorrect scaling behavior and potential runtime errors. The work centered on Python, leveraging backend development skills to ensure that scaling validation operates as intended. No new features were released during this period, as efforts prioritized code quality and risk mitigation. The targeted bug fix contributed to more robust scaling logic, supporting the stability and reliability of the system in production environments.