AI / OpenClaw Interview Questions
Describe how OpenClaw differs from a traditional chatbot?
A traditional chatbot like a standard ChatGPT-style assistant operates in a stateless request-response loop, you send a prompt, it replies, and the interaction is over.
- OpenClaw instead runs continuously, holding context and session state across an ongoing task rather than just a single exchange
- It executes multi-step workflows, making a sequence of tool calls, evaluating each result, and deciding on next steps without needing a person to prompt every single stage
- A single task can trigger anywhere from roughly three to eight LLM calls under the hood before it's actually finished
This shift, from an assistant you talk to, to an agent that does things, is exactly what both makes OpenClaw useful and raises the security stakes compared to a stateless chatbot.
How does a traditional chatbot typically operate?
Roughly how many LLM calls can a single OpenClaw task trigger?
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