This paper introduces CogniSNN, a novel Spiking Neural Network (SNN) paradigm that incorporates Random Graph Architectures (RGA) to address the limitations of traditional, rigid SNN designs. CogniSNN enhances neuron-expandability, pathway-reusability, and dynamic-configurability, leading to improved performance, robustness, and continual learning capabilities in multi-task scenarios.