Glossary
Agentic AI
Agentic AI describes systems that can take actions on a user's behalf. Instead of only answering questions, they can use tools, handle multi-step work, and adapt as they go.
Why it matters
It is the shift from AI that explains a task to AI that actually does it. That is what makes AI useful for everyday work.
How it works
Agentic systems combine language understanding with tools. They take a goal, break it into steps, call APIs or services, observe the result, and continue until the task is done or needs human input.
How OpenClaw uses this
OpenClaw is agentic AI in practice. Ask it to schedule a meeting and it can check your calendar, find a slot, create the event, and confirm back.
Why managed hosting
Deploy agentic AI without managing infrastructure
- Agentic AI needs persistent connections, memory, and planning loops. Managed hosting handles all of it so you don't run a server.
- Multi-step workflows execute on monitored infrastructure with alerting and remediation workflows. No half-completed tasks from a crashed process.
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.
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.
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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