A multi-agent system divides a task among agents with distinct roles — one retrieves, one drafts, one checks — coordinated toward a single outcome. It is genuinely more capable on complex work and genuinely harder to operate.
Where the architecture earns its keep
Specialisation helps when a task has distinct phases requiring different context. Research, synthesis and verification are different jobs, and an agent scoped to one performs it better than a single agent attempting all three. A separate checking agent catching the drafting agent's errors is a real quality mechanism rather than a marketing diagram.
When one agent is the better answer
- The task has one phase and one kind of context.
- Latency matters — coordination costs time on every step.
- The process is not documented well enough to divide into roles.
- Nobody can explain what each agent is accountable for.
Why vendors oversell this
Multi-agent architecture demos well. Diagrams with specialised roles look sophisticated in a procurement meeting, and complexity supports a larger engagement. The question worth asking is what a second agent adds that a better-scoped single agent would not — and it should be answerable in one sentence.
Knowing that agents can be composed is easy. Deciding whether your process justifies it, defining handoffs precisely enough to debug, and building observability across the chain is the work. Our analysis of agents versus chatbots covers the underlying architecture.
What this means for your business
Start with one agent scoped narrowly. Add a second only when you can name the specific failure it prevents. Complexity added before it is needed is complexity you maintain forever.