{"id":104071,"date":"2026-03-17T15:54:06","date_gmt":"2026-03-17T10:24:06","guid":{"rendered":"https:\/\/www.guvi.in\/blog\/?p=104071"},"modified":"2026-04-06T10:50:23","modified_gmt":"2026-04-06T05:20:23","slug":"build-agentic-ai-with-langchain-and-langgraph","status":"publish","type":"post","link":"https:\/\/www.guvi.in\/blog\/build-agentic-ai-with-langchain-and-langgraph\/","title":{"rendered":"How to Build Agentic AI with LangChain and LangGraph in 2026"},"content":{"rendered":"\n

You have probably used ChatGPT or any AI chatbot and noticed that it answers questions but cannot actually go out and do things on its own. Ask it to research a topic, write a report, check your database, and send a summary email, and it will tell you how to do it but will not do it for you. Agentic AI changes that completely. This tutorial on how to build agentic AI with LangChain and LangGraph will show you how to create AI that thinks, decides, and acts across multiple steps all by itself.<\/p>\n\n\n\n

In this guide, you will learn what agentic AI is, how LangChain and LangGraph work together, and how to build a real working agent from scratch with code examples written so clearly that even a beginner can follow every step.<\/p>\n\n\n\n

Quick Answer<\/strong><\/p>\n\n\n\n

Agentic AI is AI that can reason, plan, use tools, and complete multi-step tasks autonomously. You build it using LangChain, which provides the building blocks like tools and memory, and LangGraph, which connects those blocks into a stateful workflow using nodes and edges. Together they let you create AI agents that loop, branch, remember, and act on their own.<\/p>\n\n\n\n

What Is Agentic AI<\/strong><\/h2>\n\n\n\n
\"What<\/figure>\n\n\n\n

Regular AI gives you an answer. Agentic AI takes action. When you ask a regular LLM a question, it reads your prompt and generates a response. That is the end of the interaction. Agentic AI is different because it can break a goal into smaller steps, decide which tool to use at each step, execute those tools, look at the results, and then decide what to do next. It keeps going until the goal is complete.<\/p>\n\n\n\n

Think of it like the difference between asking someone for directions and hiring a travel agent. One gives you information. The other plans the trip, books the tickets, arranges the hotel, and handles problems along the way. Agentic AI is the travel agent.<\/p>\n\n\n\n

Here is something to think about:<\/em><\/strong> what tasks in your daily work require you to take multiple steps, check something, then decide what to do next based on the result? Those are exactly the tasks agentic AI is built for.<\/em><\/p>\n\n\n\n

What Is LangChain and What Is LangGraph<\/strong><\/h2>\n\n\n\n
\"What<\/figure>\n\n\n\n

Before writing any code, you need to clearly understand what each tool does and why you need both. Many beginners try to use one without the other and run into walls quickly.<\/p>\n\n\n\n

1. What LangChain Does<\/strong><\/h3>\n\n\n\n

LangChain is an open-source Python framework that gives you the building blocks to create AI-powered applications. It connects your LLM to tools like web search, databases, APIs, and file systems. It also handles prompts, memory, and the logic of how your agent should behave step by step.<\/p>\n\n\n\n

Think of LangChain as the toolbox. It has everything your agent needs to function, the LLM brain, the tools it can use, and the memory it can store things in. But a toolbox alone does not build a house. You need a blueprint for how everything connects.<\/p>\n\n\n\n