{"slug": "langchain-langgraph-concepts-you-should-know", "title": "LangChain & LangGraph Concepts You Should Know", "summary": "A developer outlines five foundational concepts in LangChain and LangGraph that AI engineers should understand: chains, tools, memory, agents, and graphs. Chains are linear pipelines for AI tasks, tools allow LLMs to interact with external systems, memory enables context retention across interactions, agents dynamically decide workflows, and graphs support branching and looping for complex autonomous agents.", "body_md": "Here are five foundational **LangChain** and **LangGraph** concepts every AI engineer should understand.\n\nA **chain** is a sequence of steps where the output of one step becomes the input of the next.\n\n**Example:**\n\n```\nUser Question\n      ↓\nRetrieve Documents\n      ↓\nLLM Generates Answer\n      ↓\nFormat Response\n```\n\nThink of it as a pipeline for AI tasks.\n\nLLMs only know what was in their training data.\n\n**Tools** let them interact with the outside world.\n\nExamples include:\n\nInstead of only generating text, the AI can now *do things*.\n\nMemory allows an AI to remember information across interactions.\n\nWithout memory:\n\n```\nUser: My name is Sam.\n...\nUser: What's my name?\n\nAI: I don't know.\n```\n\nWith memory:\n\n```\nAI: Your name is Sam.\n```\n\nMemory can be:\n\nAn **agent** doesn't follow a fixed workflow.\n\nInstead, it:\n\nExample:\n\n```\nUser:\n\"Find the latest exchange rate and calculate how much 250 USD is in KES.\"\n\nAgent:\n→ Search exchange rate\n→ Use calculator\n→ Return final answer\n```\n\nThe workflow is dynamic rather than predetermined.\n\nTraditional chains are linear.\n\nLangGraph introduces **graphs**, where execution can branch, loop, pause, or resume.\n\nExample:\n\n```\n          Start\n             │\n             ▼\n      Understand Task\n        ┌────┴────┐\n        ▼         ▼\n   Search Web   Query Database\n        │         │\n        └────┬────┘\n             ▼\n      Evaluate Results\n        ┌────┴────┐\n     Good?      No\n       │         │\n       ▼         │\n    Final Answer │\n                 │\n                 ▼\n          Try Another Tool\n```\n\nThis makes LangGraph ideal for building autonomous AI agents that can recover from errors, make decisions, and manage complex workflows.\n\nIf you're learning modern AI engineering, mastering these five concepts will give you a strong foundation for building production-ready AI applications.", "url": "https://wpnews.pro/news/langchain-langgraph-concepts-you-should-know", "canonical_source": "https://dev.to/msnmongare/langchain-langgraph-concepts-you-should-know-1la5", "published_at": "2026-07-10 05:58:30+00:00", "updated_at": "2026-07-10 06:05:32.402066+00:00", "lang": "en", "topics": ["developer-tools", "artificial-intelligence", "large-language-models", "ai-agents"], "entities": ["LangChain", "LangGraph"], "alternates": {"html": "https://wpnews.pro/news/langchain-langgraph-concepts-you-should-know", "markdown": "https://wpnews.pro/news/langchain-langgraph-concepts-you-should-know.md", "text": "https://wpnews.pro/news/langchain-langgraph-concepts-you-should-know.txt", "jsonld": "https://wpnews.pro/news/langchain-langgraph-concepts-you-should-know.jsonld"}}