Setting Up Multiple Concurrent OpenClaw Agents with Separate Memory
The Goal
I want to run multiple OpenClaw agents simultaneously, each with their own independent memory and context. These aren't sub-agents of a main agent - they're separate agents running in parallel. I need to figure out the best architecture for:
Calling/triggering agents separately
OR having a main orchestrator bot that delegates to specialized agents
Monitoring status and conversations between agents
Current Understanding
I'm trying to decide between two approaches:
Approach 1: Direct Agent Calls
Call each specialized agent directly when needed
Each agent maintains its own memory/context
I manually route tasks to the appropriate agent
Approach 2: Orchestrator Pattern
One main "router" agent that analyzes requests
Main agent delegates to specialized agents
Agents can communicate with each other through the orchestrator
I can observe the multi-agent conversation flow
Questions for the Community
What's the recommended pattern for running multiple concurrent agents in OpenClaw? Is there built-in support for agent orchestration?
Memory isolation: How do I ensure each agent maintains completely separate memory/context? Do I need separate instances, sessions, or configuration files?
Inter-agent communication: If I go with the orchestrator approach, what's the best way to:
Have agents pass information to each other
Track conversation chains between agents
Prevent infinite loops or circular delegations
Status monitoring: How can I:
See which agents are currently active/idle
View the conversation history between agents
Debug when agents aren't communicating properly
Best practices: Has anyone successfully implemented a multi-agent system with OpenClaw? What worked well and what pitfalls should I avoid?
I want to run multiple OpenClaw agents simultaneously, each with their own independent memory and context. These aren't sub-agents of a main agent - they're separate agents running in parallel. I need to figure out the best architecture for:
Calling/triggering agents separately
OR having a main orchestrator bot that delegates to specialized agents
Monitoring status and conversations between agents
Current Understanding
I'm trying to decide between two approaches:
Approach 1: Direct Agent Calls
Call each specialized agent directly when needed
Each agent maintains its own memory/context
I manually route tasks to the appropriate agent
Approach 2: Orchestrator Pattern
One main "router" agent that analyzes requests
Main agent delegates to specialized agents
Agents can communicate with each other through the orchestrator
I can observe the multi-agent conversation flow
Questions for the Community
What's the recommended pattern for running multiple concurrent agents in OpenClaw? Is there built-in support for agent orchestration?
Memory isolation: How do I ensure each agent maintains completely separate memory/context? Do I need separate instances, sessions, or configuration files?
Inter-agent communication: If I go with the orchestrator approach, what's the best way to:
Have agents pass information to each other
Track conversation chains between agents
Prevent infinite loops or circular delegations
Status monitoring: How can I:
See which agents are currently active/idle
View the conversation history between agents
Debug when agents aren't communicating properly
Best practices: Has anyone successfully implemented a multi-agent system with OpenClaw? What worked well and what pitfalls should I avoid?
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