Glossary

What Is AI Agent?

An AI agent is a system that uses an LLM to autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots that respond to prompts, agents can use tools, browse the web, execute code, manage files, and chain multiple steps together to complete complex tasks.

How AI Agent Works

An AI agent combines an LLM (the brain), tools (the hands), and memory (the context). You say 'deploy my app to production' and the agent: reads your code, runs tests, fixes failures, builds the Docker image, pushes to the registry, and updates the deployment — all autonomously.

Examples of AI agents: Claude Code (writes and runs code), Devin (software engineering agent), AutoGPT (general-purpose), and custom agents built with LangChain, CrewAI, or the Anthropic Agent SDK. Agents are the next evolution beyond chatbots.

Why Developers Use AI Agent

AI agents are transforming development workflows. They handle multi-step tasks that chatbots can't: debugging across files, implementing features, managing infrastructure, and coordinating complex workflows. Building effective agents requires understanding tool use, error handling, and guardrails.

Key Concepts

  • Tool Use — Agents call external tools (APIs, code execution, file system) to take actions beyond text generation
  • Planning — Agents break complex goals into steps, execute them in order, and adapt when things go wrong
  • Memory — Agents maintain context across interactions — short-term (conversation) and long-term (persistent storage)
  • Guardrails — Safety constraints that prevent agents from taking harmful or unauthorized actions

Building an AI Agent

python
from anthropic import Anthropic

client = Anthropic()
tools = [{
    'name': 'run_code',
    'description': 'Execute Python code',
    'input_schema': {
        'type': 'object',
        'properties': {'code': {'type': 'string'}},
        'required': ['code']
    }
}]

response = client.messages.create(
    model='claude-sonnet-4-20250514',
    max_tokens=1024,
    tools=tools,
    messages=[{'role': 'user', 'content': 'Calculate the first 20 Fibonacci numbers'}]
)
# Agent uses the run_code tool to execute Python

Learn AI Agent — Top Videos

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Frequently Asked Questions

What's the difference between a chatbot and an AI agent?

A chatbot generates text responses. An AI agent takes actions — it can browse the web, execute code, call APIs, manage files, and chain multiple steps together. Agents are autonomous; chatbots are reactive.

Are AI agents reliable enough for production?

Increasingly yes, but with guardrails. Use human-in-the-loop for critical actions, implement retry logic, set clear boundaries on what the agent can do, and monitor outputs. Claude Code and GitHub Copilot Workspace are production-grade agent systems.

Want a structured learning path?

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Related Terms

ChatGPTLLMFunction CallingVibe CodingMCP

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