Technique Updated 2026-04
AI Agent
Definition
An AI agent is an autonomous system that uses an LLM to plan, decide and execute real tasks without human intervention at each step.
See also in the glossary
L
LLM (Large Language Model)
An LLM is an AI model trained on billions of texts, capable of understanding and generating human language.
P
Prompt
A prompt is the instruction or question you give an AI to get a response. It's the interface between you and the model.
R
RAG (Retrieval-Augmented Generation)
RAG is a technique that connects an LLM to external data sources to generate more accurate and up-to-date answers.
G
Generative AI
Generative AI refers to artificial intelligence systems capable of creating original content: text, images, video, audio, code.
Tools that use ai agent
Frequently Asked Questions
What's the difference between a chatbot and an AI agent?
A chatbot answers questions in a conversation. An AI agent acts: it navigates files, executes commands, calls APIs, makes decisions and chains actions to complete an entire mission.
Are AI agents reliable?
It depends on the task. For well-defined tasks (send an email, create a file, run a search), agents are very reliable. For ambiguous or critical tasks, human oversight is still necessary.
What are the best AI agents in 2026?
OpenClaw (open source, 100K+ stars), Claude Code (development), Relevance AI (business no-code) and Activepieces (open source automation) are the most used.
What does an AI agent do?
An AI agent uses an LLM to autonomously plan, decide, and execute real-world tasks — not just generate text. It follows a perception → reasoning → action → observation loop: reading files, calling APIs, running code, browsing the web, and adapting when steps fail. Tools like OpenClaw and Claude Code can handle entire workflows, such as deploying an application or building a new feature, without requiring human input at every step.
What are the best AI agents right now?
The strongest AI agents in 2026 are OpenClaw, Claude Code, and Relevance AI. OpenClaw is the leading open-source generalist agent with 100K+ GitHub stars. Claude Code excels at autonomous software development directly in the terminal. Relevance AI targets business workflows with a no-code builder. For automation pipelines, Activepieces is also worth evaluating. The best choice depends on your use case: dev work, business ops, or custom integrations.
What are some real-world examples of AI agents?
OpenClaw is a generalist open-source agent that automates complex multi-step workflows. Claude Code operates inside the terminal to handle entire development tasks — analyzing a codebase, writing tests, and deploying code autonomously. Relevance AI lets non-technical teams build business-focused agents without coding. ActivePieces connects agents to external apps and APIs for process automation. Each represents a different use case: dev tooling, business ops, and workflow integration.
Is ChatGPT an AI agent?
No — in its standard form, ChatGPT is a chatbot, not an AI agent. It generates text responses but does not autonomously plan multi-step tasks, execute code in your environment, or interact with external systems on your behalf. However, ChatGPT with certain plugins or the Operator mode can exhibit limited agentic behavior. Purpose-built agents like OpenClaw or Claude Code go significantly further, executing real actions inside files, terminals, and APIs.
What is the difference between AI and an AI agent?
Standard AI tools like ChatGPT respond to prompts — they generate text, answer questions, and stop there. An AI agent goes further: it plans, decides, and executes multi-step tasks autonomously using tools like file systems, APIs, and browsers. Claude Code, for example, doesn't just explain how to fix a bug — it reads your codebase, writes the fix, runs tests, and iterates until the task is complete.
What are the real-world use cases of AI agents?
AI agents handle tasks across several domains: software development (Claude Code writes, tests, and deploys code autonomously), business process automation (Relevance AI builds agents that handle lead qualification, support tickets, or report generation), and general workflows (OpenClaw automates multi-step tasks like web research, file management, and API calls). Other common uses include monitoring pipelines, scheduling, data extraction, and sending emails — any repeatable task that previously required constant human oversight.
