An AI agent is an autonomous software system powered by large language models that can perceive its environment, reason about tasks, use tools, and take actions to achieve specified goals with minimal human intervention.
An AI agent is a software system that uses large language models (LLMs) as its reasoning engine to autonomously accomplish tasks. Unlike simple chatbots that respond to single prompts, agents can plan multi-step strategies, use external tools, remember context across interactions, and adapt their approach based on results. In 2026, AI agents are used in production by thousands of companies for tasks ranging from customer support to code review to data analysis.
Modern AI agents follow a perceive → reason → act loop: - Perceive — The agent receives input from its environment (user messages, API responses, file contents, web pages) - Reason — The LLM analyzes the input, considers available tools, and plans the next action - Act — The agent executes an action (call an API, write a file, run a command, search the web) - Observe — The agent reviews the result and decides whether to continue, retry, or report back This loop continues until the task is complete or the agent determines it cannot proceed.
Chatbots respond to individual messages without memory or tool access. They're reactive and stateless. Copilots assist humans in real-time (like GitHub Copilot for code). They suggest actions but don't execute autonomously. Agents operate autonomously with minimal supervision. They can plan, use tools, and execute multi-step workflows independently. OpenClaw specializes in building production-grade agents with its skill-based architecture.
OpenClaw provides the infrastructure for building, deploying, and managing AI agents: - 5,705+ pre-built skills give agents specific capabilities without custom code - Skill composition lets you combine capabilities into complex workflows - Security model ensures third-party skills are reviewed and safe - Production features include retry logic, rate limiting, and observability Install OpenClaw and start building: `npx clawhub@latest install`
Yes, when properly configured with guardrails. OpenClaw provides security scanning, permission systems, and human-in-the-loop options to ensure agents operate safely in production environments.
RPA (Robotic Process Automation) follows rigid, pre-defined rules. AI agents use LLMs for flexible reasoning and can handle ambiguous situations, adapt to changes, and process unstructured data.
Costs depend on LLM usage. A typical OpenClaw agent workflow costs $0.01-$0.50 per execution depending on the models and skills used. Local models via Ollama can reduce costs to near-zero.