What is Multi-Agent System?

One agent with fifty tools and a thousand-line prompt tends to get worse, not better. A multi-agent system divides the job: a supervisor breaks a request into parts and hands each to a sub-agent with its own narrow instructions and tool set — one for research, one for drafting, one for scheduling — then combines what comes back. Each sub-agent gets a clean context window and a smaller decision space, which is usually why the ensemble beats the monolith.

The costs are real: hand-offs lose information, and a supervisor that mis-delegates fails quietly. Velaris builds agents on LangGraph, where the coordination is an explicit graph — nodes, state and edges you can inspect — rather than agents improvising at each other in free text. The capability mesh reduces the pressure to split purely for tool-count reasons, since an agent searches for the tools a step needs instead of holding them all; you split for specialisation, not to dodge a prompt limit.