𝗪𝗵𝗮𝘁 𝗔𝗿𝗲 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀?

I once asked ChatGPT to plan a trip to Istanbul. It gave me a great plan. But it could not book the flights. It could not check hotel prices. It could not send an email.

The model was smart, but it had no hands. It could think, but it could not act.

AI agents solve this problem.

Standard LLMs (Large Language Models) work like a well-read assistant. You send a prompt, and the model sends a response. That is a single round trip. The model does not browse the web, check your calendar, or take actions in the real world.

An AI agent is different. An agent uses a language model to decide how to use tools to reach a goal.

An agent can:

  • Search the web
  • Run code
  • Query a database
  • Send emails
  • Use external APIs

The main difference is autonomy. You give an agent a goal, and it figures out the steps.

Comparison: • Regular LLM: Answers questions, single response, no tools, reactive. • AI Agent: Takes action, multi-step reasoning, uses tools, goal-driven.

Most agents use a pattern called ReAct (Reason and Act). It follows a simple loop:

  1. Thought: What do I need to do next?
  2. Action: Use a tool.
  3. Observe: Look at the result.
  4. Repeat: Continue until the goal is met.

Building these loops is difficult. You must handle errors, manage memory, and connect tools.

This is why frameworks like LangChain exist. LangChain provides the plumbing. It gives you pre-built tools, memory, and ways to connect models to the real world.

If your workflow is complex, you use LangGraph. LangGraph helps you build agents that can branch into different paths, run tasks in parallel, or loop back to earlier steps.

Summary:

  • LLMs respond to text.
  • Agents use tools to complete tasks.
  • The ReAct loop drives agent logic.
  • LangChain manages the connection between models and tools.
  • LangGraph handles complex, branching workflows.

In my next post, I will show you how to set up your environment and run your first agent.

Source: https://dev.to/ikram_khan/what-are-ai-agents-a-plain-english-introduction-56nd

Optional learning community: https://t.me/GyaanSetuAi