It's tempting to throw a multi-agent team at every problem. More agents means better results, right? Not always. Understanding when to use agent teams — and when a single well-crafted prompt does the job — is the difference between elegant automation and unnecessary complexity.
A single agent excels when the task is self-contained and linear. If you can describe the entire job in one prompt and the output doesn't require cross-referencing multiple domains of expertise, a single agent is faster, cheaper, and simpler.
Good single-agent tasks:
The key signal: if there's no meaningful disagreement or parallel work to be done, skip the team.
Multi-agent teams earn their overhead when the problem has natural decomposition points — where different parts of the work benefit from different perspectives, expertise, or parallel execution.
When a problem spans multiple fields (market research + financial modeling + competitive intelligence), each agent can specialize. A market analyst agent thinks differently than a financial modeler, and that diversity produces richer output.
When mistakes are expensive, the Advisory Debate pattern lets agents challenge each other's reasoning. One agent drafts, another critiques, a third synthesizes. The result is more robust than any single pass.
When you need results fast, Parallel Workers or Fork-Join patterns let multiple agents work simultaneously. A competitive analysis that takes 10 minutes with one agent might take 3 minutes with four agents working in parallel.
When work flows through distinct phases — research, analysis, synthesis, review — a Sequential Pipeline ensures each phase gets dedicated attention and clean handoffs.
A useful rule of thumb: if your task description naturally breaks into 3+ distinct subtasks that could be assigned to different specialists, use a team. If it doesn't, use a single agent.
Before generating a team, ask yourself:
If you answered yes to two or more, an agent team will likely outperform a solo agent. If not, keep it simple.