This paper presents the SANDMAN architecture for cyber deception, employing Language Agents to create convincing human simulacra. These "Deceptive Agents" serve as advanced cyber decoys, designed to engage attackers to extend the observation period of attack behaviours. This research demonstrates the viability of persona-driven Deceptive Agents to generate plausible human activity to enhance the effectiveness of cyber deception strategies. Through experimentation, measurement and analysis, we illustrate how a prompt schema induces specific "personalities", defined by the five-factor model of personality, in Large Language Models to generate measurably diverse, and plausible, behaviours.