AI agent
What is an AI agent?
Definition
An AI agent is a software system that uses a large language model as its reasoning engine to pursue a goal autonomously: it plans steps, calls external tools or APIs, observes the results and decides what to do next — repeating this loop until the task is done.
Table of contents
An AI agent is a program that turns a large language model (LLM) from a text generator into something that can actually get things done. Instead of just answering a single prompt, it works toward a goal over many steps, using tools to interact with the real world.
How an AI agent works
At its core, an agent runs a loop often described as "reason → act → observe":
- Reason: the LLM decides what step is needed next to reach the goal.
- Act: it calls a tool — a database query, an API, a web search, sending an email.
- Observe: it reads the result and feeds it back into its reasoning.
This loop repeats until the goal is reached or a stop condition (a budget, a step limit) is hit. That autonomy is what separates an agent from a one-shot chatbot reply.
Agent vs. chatbot
A chatbot responds to one message at a time. An agent has a goal, memory, tools and the ability to act over multiple steps without a human in between each one. A deeper comparison is in AI agent vs. chatbot.
Building blocks
- Model: the LLM that does the reasoning.
- Tools: functions the agent may call (APIs, search, code execution).
- Memory & context: often backed by retrieval (RAG) and a vector database.
- Guardrails: limits on cost, permissions and which actions are allowed.
Examples in business
A support agent that reads the knowledge base and drafts a reply; a sales agent that qualifies inbound leads and writes them into the CRM; an operations agent that monitors systems and opens tickets. In production these run inside guardrails for privacy and cost — the hard part is reliability, not the demo.
Summary
An AI agent is an LLM given goals, tools and a loop. It is the difference between AI that talks and AI that does the work. Building agents that run reliably in production — monitored and GDPR-compliant — is exactly the engineering this site is about.
Frequently asked questions
Is an AI agent the same as ChatGPT?
No. ChatGPT is primarily a chat interface to a language model. An AI agent uses such a model as its engine but adds goals, tools and an autonomous action loop so it can complete multi-step tasks, not just answer questions.
Do AI agents work without human supervision?
They can run autonomously between steps, but production agents are deployed with guardrails: permission limits, cost budgets and monitoring. Critical actions often still require human approval.
More from the Wiki-Lexikon
AI agent vs. chatbot — what’s the difference?
A chatbot answers messages; an AI agent pursues a goal — planning, using tools and taking action over multiple steps. The clear difference, with examples and when to use each.
What is an LLM (large language model)?
A large language model (LLM) is an AI trained on huge amounts of text to predict and generate language. Definition, how it works, tokens, context window and where the limits are.
What is MCP (Model Context Protocol)?
MCP (Model Context Protocol) is an open standard that lets AI models connect to tools and data sources through one consistent interface. Definition, how it works and why it matters for AI agents.
What is AI automation?
AI automation uses language models and AI agents to handle tasks that need understanding and judgment — not just fixed rules. Definition, how it differs from classic automation, and real examples.