Developed and delivered a benchmark progress visualization feature for the kaiyux/TensorRT-LLM repository, focusing on enhancing transparency during performance benchmarking. Integrated the tqdm library into the Python-based benchmark utility to provide real-time progress feedback as each performance item was registered. This approach improved observability for long-running benchmarks, enabling developers to monitor progress and make informed decisions during performance analysis and tuning. The work demonstrated proficiency in asynchronous programming, benchmarking, and performance analysis, with an emphasis on instrumentation-driven workflow improvements. No major bugs were addressed during this period, as the primary focus remained on feature implementation and enhancing developer productivity through better tooling.