AI / OpenClaw Interview Questions
What is the difference between OpenClaw's multi-agent support and running a single agent instance?
| Single agent instance | Multi-agent setup via agents.list |
| One shared workspace, tool policy, and model for everything | Each agent has its own workspace, tool policy, and model |
| Simpler to configure and reason about | More setup, but enables role-based permission separation |
| A compromise or mistake affects the agent's full permission set | A compromise is contained to whatever that specific agent was granted |
| Fine for a single user handling varied personal tasks | Better suited to teams needing distinct roles, like sales versus DevOps |
Multi-agent support is really a permissions tool as much as a functionality one, splitting responsibilities across agents is how OpenClaw applies least-privilege thinking at the deployment level rather than the individual tool-call level.
What does a single agent instance share across all tasks?
What does multi-agent support primarily function as?
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