Multi-Agent Systems: When One Agent Isn't Enough

Multi-agent systems are having a moment, and like every moment in this field, that means teams are building them for problems a single well-scoped agent would have solved in a fraction of the time and cost. Before splitting a system into a "planner" and three "specialist" agents talking to each other, there is one question worth answering honestly: is the task actually separable, or does it just feel more impressive with more agents in the diagram?

The real signal for splitting

The honest trigger for multi-agent architecture is context, not complexity. When a single loop needs more distinct context, tools and expertise than fits reliably in one prompt — a research step needing web access, a compliance step needing a completely different knowledge base, a drafting step needing brand voice — splitting into specialists that each hold less and do it better beats one overloaded generalist agent.

The cost nobody puts in the pitch deck

• Coordination overhead — every hand-off between agents is a place meaning can be lost or a loop can form.
• Debugging difficulty — a bug can live in the orchestration logic, in any individual agent, or in the interface between them; tracing it takes real tooling.
• Cost multiplication — three agents making LLM calls to solve what one could solve is three times the token spend, minimum.
• Latency stacking — sequential agent hand-offs add up fast; a five-second single-agent task becomes a twenty-second multi-agent one.

None of that means multi-agent systems are wrong — for genuinely separable, high-value workflows (our own Insight Agent splits retrieval, SQL generation and narration into distinct steps for exactly this reason) they outperform a single agent by a wide margin. It means the split has to earn its overhead.

Design the failure mode of the orchestrator first

The orchestrator — whatever decides which agent runs next — is the single point of failure in the system. If it stalls, loops, or mis-routes, every sub-agent underneath it looks broken even if each one works perfectly in isolation. We build and load-test the orchestrator's failure paths (timeouts, retries, a hard step ceiling) before we polish a single specialist agent, because that is where production incidents actually originate.