Question 1

Can workers communicate directly with each other?

Accepted Answer

Not by default, and we recommend against it. Worker-to-worker communication creates lateral movement paths. If worker A can send data to worker B, a compromised worker A can attack worker B through its communication channel. The supervisor-worker pattern routes all inter-agent communication through the supervisor, which acts as a checkpoint. If you must enable direct worker communication, create a dedicated internal message bus with its own YAML policy and audit logging.

Question 2

Which framework is best for NemoClaw multi-agent?

Accepted Answer

CrewAI provides the most natural mapping to the supervisor-worker pattern and has explicit NemoClaw documentation via the CrewAI blog. LangChain offers the most flexibility for custom orchestration logic. LlamaIndex is strongest for RAG-heavy workflows where workers retrieve and synthesize documents. Semantic Kernel integrates best with Microsoft ecosystem tools. For detailed framework comparisons, sparkco.ai published a head-to-head analysis of LangChain vs. AutoGen vs. CrewAI vs. OpenClaw, and o-mega.ai covers "LangGraph vs CrewAI vs AutoGen: Top 10 AI Agent Frameworks" with benchmark data. Choose based on your existing framework expertise and the specific workflow patterns your agents implement.

Question 3

How do I handle worker failures in production?

Accepted Answer

The supervisor should implement retry logic with exponential backoff for worker failures. NemoClaw's sandbox health check (nemoclaw sandbox health <sandbox-id>) returns the sandbox status, which the supervisor can poll before dispatching tasks. For critical workflows, configure dead letter queues: tasks that fail after N retries are routed to a human review queue rather than dropped. Our managed deployments include automated sandbox restart on failure with Slack/PagerDuty alerting.

Question 4

Can I run multi-agent NemoClaw on a single machine?

Accepted Answer

Yes, for development and small deployments. A machine with 32 GB RAM and 8 CPU cores can run a supervisor and 3-4 workers comfortably. Each sandbox consumes approximately 1-2 GB RAM at idle. For production with more than 5 concurrent workers, distribute across multiple machines and use NemoClaw's gateway clustering (when available) or a load balancer in front of multiple NemoClaw instances.

Tag: Multi-Agent

NemoClaw Multi-Agent Deployment: Supervisor + Worker Architecture in Production