智能体 / NAVIN RESEARCH
Start With One AI Agent Before Building a Multi-Agent System
A practical decision rule for choosing one agent, a workflow, or several collaborating agents.
A practical decision rule for choosing one agent, a workflow, or several collaborating agents.
简要回答: Use one agent until evaluation data shows that context size, tool ownership, or parallel work is the actual bottleneck. Multiple agents add coordination, latency, cost, and new failure modes; they are an architecture choice, not an automatic quality upgrade.
实施步骤
- Write one measurable task contract with inputs, allowed actions, and a stop condition.
- Build a deterministic workflow around one model and the smallest useful tool set.
- Collect failures by type: missing knowledge, bad tool choice, context overload, or independent subtasks.
- Split roles only when a recorded failure maps clearly to separation or parallelism.
验证清单
- Compare task success, p95 latency, and token cost against the single-agent baseline.
- Verify that every handoff has a schema and an owner.
- Keep a fallback path that can finish or safely stop when one specialist fails.
常见错误
- Creating personas without distinct tools or information.
- Letting agents converse without a turn or budget limit.
- Judging an architecture from a polished demo instead of repeated tasks.
实际决策
先交付能够通过上述检查的最小设计。记录测试中使用的模型、提示词、工具、数据集与运行时版本，让后续变化可以被比较而不是被猜测。依赖供应商的限制、模型名称、价格或预览功能之前，请重新检查链接文档；这些细节变化往往快于本文的工程原则。
