Single-Agent vs Multi-Agent
A single-agent system uses one AI Agent to handle the whole task. A multi-agent system uses several agents, where each one focuses on a different role.
Playground
Same task, one agent or many
Pick a mode and watch how the same task flows through one agent or a team of agents.
Mode
Who is on the job
Run the task
Step 0 of 5
When one agent is enough
Simple tasks, one agent
For short, clear jobs, a single agent handles everything with no extra help.
Small task
"Summarize this paragraph."
Clear task
"Draft a short email."
Few steps
"Convert notes into bullet points."
One agent is often enough for simple tasks.
When multiple agents help
Complex work, a team of agents
When a task is large or needs several skills, splitting it across agents can help.
Complex task
"Create a full research report."
Different skills
"Research, write, review, and improve."
Quality check
"One agent creates, another reviews."
Multiple agents help when the task needs different roles or repeated checking.
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Key takeaways
- • A single-agent system uses one agent.
- • A multi-agent system uses multiple agents.
- • One agent is enough for many simple tasks.
- • Multiple agents can divide complex work.
- • Multi-agent systems shine when different roles are needed.
Summary
Single-agent systems are simple and useful for many tasks. Multi-agent systems are useful when work can be split across different roles.