Agentic AI
AI systems that can take autonomous actions, make decisions, and use tools to accomplish goals. Unlike chatbots that only respond to prompts, agentic AI proactively performs multi-step tasks, adapts to results, and operates with minimal human oversight.
Agent Framework
Software infrastructure that enables building and running AI agents. An agent framework provides the scaffolding for tool integration, memory, scheduling, and model connectivity. Examples include OpenClaw, LangChain, and AutoGPT.
API (Application Programming Interface)
A standardized way for software programs to communicate with each other. AI agents use APIs to connect to AI models (like Claude or GPT-4o), send prompts, receive responses, and interact with external services such as email, CRM, and calendar platforms.
Chain of Thought (CoT)
A reasoning technique where the AI model shows its step-by-step thinking process before delivering a final answer. CoT prompting improves accuracy on complex tasks by forcing the model to break problems down logically rather than jumping to conclusions.
ClawHub
OpenClaw's marketplace for agent skills and plugins. Similar to an app store for AI agent capabilities, ClawHub lets you browse, install, and share modular skills that extend what your OpenClaw agent can do.
Context Window
The maximum amount of text an AI model can process in a single conversation. Measured in tokens (roughly 4 characters per token), the context window determines how much prior conversation and reference material the model can "see" at once. Claude Sonnet 4.5 supports 200K tokens, while GPT-4o supports 128K.
Docker
A containerization platform that packages applications and their dependencies into isolated, portable containers. Docker is recommended for running OpenClaw securely in production because it prevents the agent from accessing files or processes outside its container.
Fallback Chain
A sequence of AI model providers configured so that if the primary provider fails (due to rate limits, downtime, or errors), the next provider in the chain automatically handles the request. OpenClaw's Maton Gateway supports fallback chains for reliable uptime.
Function Calling (Tool Use)
The ability of an AI model to invoke external functions, APIs, or tools during a conversation. Instead of only generating text, the model can call a function to check a database, send an email, or fetch live data. This capability is critical for agentic workflows.
Gateway (Maton Gateway)
OpenClaw's model router that manages provider selection, fallback chains, and request routing. The Maton Gateway sits between your agent and AI model providers, handling load balancing, cost optimization, and automatic failover.
Heartbeat Scheduling
A feature that makes AI agents proactive by running tasks on a schedule (for example, every morning at 8am) rather than waiting for user commands. Heartbeat scheduling transforms a reactive chatbot into an autonomous agent that checks inboxes, generates reports, and follows up on leads automatically.
Inference
The process of an AI model generating a response to an input prompt. "Running inference" means sending text to the model and receiving output. Inference costs are typically measured per million tokens (MTok) and vary by provider and model size.
JSON Configuration (openclaw.json)
OpenClaw's primary configuration file that defines the AI provider, model, API keys, and agent settings. This JSON file controls which model your agent uses, how it connects to providers, and what features are enabled. It is the single source of truth for agent behavior.
LLM (Large Language Model)
The AI models that power agents. LLMs are trained on massive text datasets and can generate human-like text, reason about problems, and follow instructions. Examples include Claude (Anthropic), GPT-4o (OpenAI), Llama (Meta), and DeepSeek.
MCP (Model Context Protocol)
An open standard created by Anthropic for connecting AI models to external tools and data sources. MCP provides a universal interface so that any compatible tool can work with any compatible model. OpenClaw uses MCP for skill integration and tool connectivity.
Memory (Agent Memory)
The system that allows an AI agent to remember context across conversations and sessions. OpenClaw uses MEMORY.md files for persistent memory, storing facts, preferences, and learned patterns so the agent retains knowledge between interactions.
Mixture of Experts (MoE)
An AI architecture where only a subset of the model's parameters activate for each inference request, improving efficiency without sacrificing quality. MoE models route each input to specialized "expert" sub-networks. DeepSeek V3 and Kimi K2 use this architecture.
Multi-Agent System
Multiple AI agents working together, each with specialized roles and responsibilities. Instead of one agent doing everything, a multi-agent system divides tasks among specialists. OpenClaw supports coordinating multiple agents as a "council" for complex workflows.
Ollama
An open-source tool for running AI models locally on your computer. Ollama simplifies downloading, managing, and serving models like Llama and DeepSeek. It connects to OpenClaw for free, private inference with no API costs and full data privacy.
OpenRouter
A unified API gateway that provides access to multiple AI model providers (Claude, GPT, DeepSeek, and others) through a single API key. OpenRouter simplifies provider management and lets you switch models without changing your code.
Prompt Injection
A security attack where malicious text tricks an AI agent into performing unintended actions. For example, an attacker might embed hidden instructions in a document that cause the agent to leak data or execute harmful commands. Proper input sanitization and sandboxing help mitigate this risk.
Quantization
A technique for compressing AI models to use less memory and run faster, with a small quality trade-off. Quantization reduces the precision of model weights (for example, from 16-bit to 4-bit). Common formats include Q4_K_M, INT4, and GPTQ.
RAG (Retrieval-Augmented Generation)
A technique where the AI agent retrieves relevant documents from a knowledge base before generating a response. RAG improves accuracy by grounding the model's output in real data rather than relying solely on its training. It is especially useful for domain-specific questions.
Skill (OpenClaw Skill)
A modular capability that extends what an OpenClaw agent can do. Skills are self-contained packages that add specific functionality, such as browsing the web, sending emails, managing files, or integrating with third-party services. Skills are installed from ClawHub.
Soul (soul.md)
OpenClaw's personality and behavior configuration file. The soul.md file defines how the agent communicates, what boundaries it respects, and its overall operating style. It shapes tone, formality, guardrails, and the agent's identity across all interactions.
Token
The basic unit of text processed by AI models. One token is roughly 4 English characters or 0.75 words. AI model pricing is typically quoted per million tokens (MTok). Understanding token counts helps estimate costs and manage context window limits.
Tool Use
See Function Calling. Tool use is the general term for an AI model's ability to invoke external tools, APIs, or functions. It is the foundation of agentic behavior, allowing models to take actions beyond generating text.
VPS (Virtual Private Server)
A remote cloud server for running always-on OpenClaw deployments. A VPS provides dedicated resources, a static IP address, and 24/7 uptime so your agent can run continuously. Popular providers include DigitalOcean, Hetzner, and Contabo.
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