Agents & Tools · intermediate
Agent (AI agent)
An AI agent is an LLM-driven system that decides which actions to take, executes them via tools, observes the results, and iterates until a goal is met.
Explanation
A pure chatbot only talks. An agent talks, then runs code, makes API calls, browses the web, edits files, queries databases — whatever its tools let it do. The model is the planner and the controller; the tools do the actual work.
The pattern is usually some form of ReAct: think, act, observe, repeat. Around it sit a tool registry, an execution environment (often sandboxed), memory, and safety guardrails. Modern frameworks: OpenAI Agents SDK, Anthropic's Claude Agent SDK, LangGraph, AutoGen.
Agents fail in ways pure chat does not: infinite loops, expensive tool calls, prompt injection from tool outputs. Production agents add timeouts, cost caps, and human-in-the-loop checkpoints.
Examples
- Claude Code — coding agent that edits files, runs commands, runs tests.
- A research agent that browses, takes notes, and produces a report.
Frequently asked
What is Agent?
An AI agent is an LLM-driven system that decides which actions to take, executes them via tools, observes the results, and iterates until a goal is met.
What is an example of agent?
Claude Code — coding agent that edits files, runs commands, runs tests.
How is Agent related to Tool Use?
Agent and Tool Use are both agents & tools concepts. Tool use is when an LLM can call external functions — APIs, code interpreters, databases, web fetchers — and read their results. The mechanism that turns chat into action.
Is Agent considered intermediate?
Agent is generally considered intermediate-level material in the AI and LLM space.