Traditional robotic systems are built on carefully planned connection topologies linking sensors, actuators, and controllers. While this approach enables precise control, it also makes such systems vulnerable to noise, component failures, and unexpected task conditions. In contrast, many natural and synthetic collectives, from active gels to insect swarms, rely on stochastic local mechanical interactions, rather than permanent configurations, to achieve capabilities and resilience far beyond those of any individual. We introduce the Cross-link collective, a robotic analog to active gels, demonstrating that global functionality can emerge from the mechanical intelligence of the modules and their stochastic interactions. Supported by both experimental data and comparative modeling, this research demonstrates that the Cross-link collective naturally evolves into configurations that optimize locomotion, while simultaneously self-regulating phase drift and internal torques purely through physical interactions. This research provides a foundational framework for the future development of highly resilient robotic systems. As robots become increasingly pervasive in unstructured, unpredictable settings from infrastructure and agriculture to search-and-rescue, harnessing such inherently adaptive strategies in the design and deployment of robotic systems will be the key to ensuring reliable performance.