Here are a few practical reasons for multi-agent systems:

1. LLMs handle narrower, simpler instructions better - decomposing into multiple agents improves reliability (related to instruction following accuracy).

2. Similarly, tool-calling accuracy improves when each agent has a smaller set of specific tools assigned to them.

3. Smaller agents mean prompt changes (which aren't very deterministic) can be isolated and tested more easily.

4. Dividing agents by task enables stronger, more precise guardrails for real-world use cases.

Happy to discuss further!