AI / OpenClaw Interview Questions
Explain the lifecycle of a task from a chat message to a completed OpenClaw agent response?
flowchart LR
A[Message Sent via WhatsApp/Telegram/etc] --> B[Channel Adapter]
B --> C[Gateway Control Plane]
C --> D[Agent Runtime: reasoning loop]
D --> E[Tool Dispatch]
E --> F[Tool Execution: sandboxed if configured]
F --> D
D --> G[Response Delivery via Channel Adapter]
G --> H[Session State Persisted]
- Message received: a user sends a message through a supported channel, like WhatsApp or Slack, and the corresponding channel adapter receives it
- Routing: the Gateway control plane routes that message, internally as a node.invoke frame, to the Agent Runtime handling that session
- Reasoning: the Agent Runtime's LLM reasoning loop processes the message and decides whether a tool call is needed
- Tool dispatch and execution: if a tool is needed, the call is dispatched to the Tool Layer, executed, optionally inside a sandbox, and the result returned
- Iteration: the agent factors that result into its next reasoning step, repeating tool calls as needed, typically three to eight LLM calls for a full task
- Response delivery: once the task is complete, the response is formatted for the originating platform and sent back through the appropriate channel adapter
- State persistence: the session index and per-session transcript are updated so the conversation's context carries forward
This lifecycle is what turns a single chat message into a genuine multi-step, tool-using task rather than a single one-shot reply.
What receives an incoming message first in this lifecycle?
What is updated at the very end of this lifecycle?
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