Interactions between agents are supported through a continuous process of detecting and responding to behaviors that are contingent upon the other agent's behavior. Here, we explore the temporal dependence of these mechanisms, focusing on the role of timescale compatibility in inter-agent interactions. Using continuous-time recurrent neural networks (CTRNNs) to control embodied agents in a minimal social interaction task, we demonstrate that effective interactions require agents to operate on compatible timescales. Our results indicate that time scale mismatches disrupt agents’ ability to distinguish other agents from non-social entities, revealing a timescale threshold beyond which agents begin misclassifying slower agents as static objects and faster agents as non-social animate objects.