Wouldn't it be better just to stack functionalities of multiple agents into a single agent instead of getting this multi-agent overhead/failure? Many people in academia consider multi-agentic systems to be just an artifact of the current crop of LLMs but with longer and longer reliable context and more reliable calls of larger numbers of tools in recent models multi-agentic systems seem less and less necessary.
In some cases, you might actually want to cleanly separate parallel agents' context, no? I suppose you could make your main agent with stack functionalities responsible for limiting the prompt of any subagents it spawns.
My hunch is that we'll see a number of workflows that will benefit from this type of distributed system. Namely, ones that involve agents having to collaborate across timezones and interact with humans from different departments at large organizations.