Best of Langchain — September 2025

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·35w

    The Open-source RAG Stack

    A comprehensive guide to building production-ready RAG systems using open-source tools. Covers the complete technology stack from frontend frameworks to data ingestion, including LLM orchestration tools like LangChain and CrewAI, vector databases like Milvus and Chroma, embedding models, and retrieval systems. Also showcases 9 practical MCP (Model Context Protocol) projects for AI engineers, ranging from local MCP clients to voice agents and financial analysts.

  2. 2
    Article
    Avatar of langchainLangChain·37w

    Building LangGraph: Designing an Agent Runtime from first principles

    LangGraph was designed as a low-level agent framework prioritizing production readiness over ease of getting started. Built to address LangChain's feedback about customization and scaling challenges, it focuses on six core features: parallelization, streaming, task queues, checkpointing, human-in-the-loop capabilities, and tracing. The framework uses a structured execution model based on the Pregel algorithm with channels and nodes, enabling deterministic concurrency and fault tolerance. Performance scales gracefully with agent complexity while maintaining low latency, making it suitable for production deployments at companies like LinkedIn, Uber, and Klarna.

  3. 3
    Article
    Avatar of telerikTelerik·34w

    Build an LLM Chat App Using LangGraph, OpenAI, Python—Part 1

    A beginner-friendly guide to building an AI chat application using LangChain, OpenAI's GPT-3.5-Turbo, and Python. Covers setting up dependencies, environment variables, creating basic chat functionality with streaming responses, handling user input in a loop, and constraining model responses to specific JSON datasets using system prompts.

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    Article
    Avatar of langchainLangChain·36w

    How to turn Claude Code into a domain specific coding agent

    LangChain researchers tested different configurations of Claude Code to improve its performance on domain-specific libraries like LangGraph. They found that high-quality, condensed documentation (Claude.md) combined with tools for accessing detailed information produced the best results. Simply providing raw documentation access didn't improve performance as much as expected and filled up the context window faster. The study used a comprehensive evaluation framework testing functionality, task requirements, and code quality across three different coding tasks.

  5. 5
    Article
    Avatar of do_communityDigitalOcean Community·35w

    Getting Started with Agentic AI in LangGraph

    LangGraph is an open-source framework built on LangChain that enables developers to create structured, reliable agentic AI systems using graph-based workflows. Unlike traditional chatbots that provide static responses, agentic AI can reason through problems, make autonomous decisions, and execute multi-step actions. The framework represents AI workflows as nodes (tasks like reasoning or tool usage) connected by edges (decision flows), providing better control and predictability than linear approaches. The tutorial covers setting up LangGraph, building basic agent workflows with state management, and demonstrates practical examples including a calculator agent and a search-enabled reasoning system.

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