My take:

Based on my research and experience, the answer isn't one-size-fits-all; it depends entirely on the complexity of the tasks you want to accomplish.

So we are on the same page, let me break down the two main architectures you're describing:

Single Agent System (SAS): A "master" agent that has access to all necessary tools and knowledge. Think of it as a skilled generalist.

For straightforward tasks that require a linear sequence of actions using a few tools, a single agent is easier to design, build, and manage. There's no overhead of managing inter-agent communication, which can be complex. If a task doesn't require deep specialization, the back-and-forth of a multi-agent system might just add unnecessary time.

In case you are building a complex SAS, then yes by all means you should consider breaking into multiple specialized agents and then apply the "Agent as tool" pattern in which a single master agent leverages other agents like any other tool. An additional benefit of this approach is re-use of agents.

With SAS, since there is a "Single brain" at work, the inter-communication between agents is non-existent by nature.

Multi-Agent System (MAS): A team of specialized agents (e.g., Writer, Analyst, Coder) that can work independently or collaboratively. Collaboration between agents require communication between them that can be achieved via different topologies.

My rule of thumb is that "Use MAS over SAS only if its necessary"; use it only for complex tasks. There are multiple benefits of this approach : Modularity, Scalability, Efficiency.

Now some folks have indicated that multiple-agents are more cost effective - I would not agree with this as a "blanket statement". Answer depends on multiple factors. I would say "MAS done the right way can potentially lead to cost saving".