Surgical cameras are used in arthroscopic surgery to reduce the invasiveness of the procedure. These arthroscopic cameras heavily rely on high-quality visualization inside joints, such as the shoulder or knee, where surgeons depend entirely on camera feedback to guide surgical instruments. This reliance on the visual systems means that these cameras must undergo rigorous reliability testing so that the equipment can be confidently used in clinical environments without worry of any malfunctions, especially during surgical procedures. Reliability testing, usually done manually, is both time-consuming and physically demanding for engineers, who must collect a large sample of reliability test data to detect any possible malfunctions. Manual testing also introduces unexpected variability, which can, in turn, make the collected data unreliable. Project Mockingbird is an autonomous reliability testing system that controls the camera’s position to run repeated surgical simulations using precise yet intentionally varied control parameters. When an edge case reveals a potential failure mode, the exact motion can be replayed, allowing engineers to isolate the cause, analyze it, and fix the issue with confidence.