In agent systems, different (autonomous) agents collaborate to execute complex tasks. Each agent provides a set of useful capabilities, and the agent system combines these capabilities as needed to perform complex tasks, based on the requests input into the system. Agent communication languages (ACLs) allow agents to communicate with each other about how to partition these tasks, and to specify the responsibilities of the individual agents that are invoked. Current ACLs make certain assumptions about the agent system, such as the stability of the agents, the lifetime of the tasks and the intelligence of the agents in the system, etc. These assumptions are not always applicable in information-centric applications, since such agent systems contain unreliable agents, very long running tasks, agents with widely varying levels of sophistication, etc. Furthermore, not all agents may be able to support intelligent planning towork around these issues, and precanned interactions used in more component-based systems do not work well. Thus, it becomes important that proper support for task coordination be available to these agent systems. In this paper we explore issues related to coordinating large, complex, long running tasks in agent systems. We divide these issues into the following categories: tasks, roles, and conversations. We then discuss how these issues impose requirements on ACL, and propose changes to support these requirements.