Agent-based computing represents an exciting new synthesis for both Artificial Intelligence and, more generally, Computer Science. It has the potential to improve the theory and the practice of modelling, designing and implementing complex computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. To rectify this situation, this paper aims to tackle exactly this issue. The standpoint of this analysis is the role of agent-based software in solving complex, realworld problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level interactions, and that can operate within flexible organisational structures.