Glossary
Large Language Model (LLM)
A large language model (LLM) is a model trained on huge amounts of text so it can understand language, follow instructions, and generate responses.
Why it matters
LLMs are the reasoning layer behind modern AI assistants. They turn natural-language requests into useful output or actions.
How it works
An LLM learns patterns from large text datasets. At runtime it predicts the next token based on your prompt and prior context.
How OpenClaw uses this
OpenClaw uses an LLM as its reasoning engine. You choose the model, and OpenClaw uses it to interpret requests, decide which tools to call, and generate responses.
Why managed hosting
Use any LLM without managing API keys yourself
- Choose your LLM from a dashboard. API keys encrypted and isolated, not sitting in a plaintext .env file on your server.
- Switch models or update API versions without redeploying. Rate limits and fallbacks handled automatically.
Related terms
AI Agent
An AI agent is software that can interpret a goal, decide what to do, and take actions with tools or external systems.
Prompt Engineering
Prompt engineering is the practice of designing prompts so a model produces more reliable and useful outputs.
Model Context Protocol (MCP)
MCP is an open standard for connecting AI models and agents to external tools, data sources, and services.
Learn more
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