LangChain

76 articles

January 13, 2026·AI & Engineering

The Architecture of Control: Building Deterministic AI Agents with LangChain and LangGraph

A complete guide to building predictable, production-ready AI agents. Learn why deterministic routing, structured outputs, and state machines are mandatory for enterprise AI.

January 6, 2026·Artificial Intelligence

The Secure Brain: Building Role-Based RAG Architectures from Ingestion to Retrieval

Data privacy is the #1 hurdle for enterprise AI. Learn how to architect a production-grade Role-Based RAG system that ensures users only see what they are authorized to access, from ingestion to real-time retrieval.

December 21, 2025·AI Security

Module 17 Lesson 1: Orchestrator Risks

The glue that breaks. Learn how framework orchestrators like LangChain and LlamaIndex introduce new security vulnerabilities through complex chaining and data handling.

December 21, 2025·AI Security

Module 17 Lesson 2: Securing LangChain

Hardening the chains. Learn specific security configurations for LangChain Agents, including sandboxing, tool limiting, and secure memory management.

December 21, 2025·AI Security

Module 17 Lesson 5: Framework-Specific Exploits

Poking the glue. Learn how to identify and test for vulnerabilities unique to LangChain, LlamaIndex, and other AI orchestration frameworks.

December 21, 2025·Automation

Module 10 Lesson 1: AI & LangChain in n8n

The intelligent workflow. Learn how n8n uses LangChain to connect AI models to your data, enabling 'Smart' automations that can read, think, and decide.

December 20, 2025·Generative AI

Module 5 Lesson 3: Agentic AI and Orchestration

From Chatbot to Coworker. Understanding AI agents that can use tools and make autonomous decisions.

LangChain

The Architecture of Control: Building Deterministic AI Agents with LangChain and LangGraph

The Secure Brain: Building Role-Based RAG Architectures from Ingestion to Retrieval

Module 17 Lesson 1: Orchestrator Risks

Module 17 Lesson 2: Securing LangChain

Module 17 Lesson 5: Framework-Specific Exploits

Module 10 Lesson 1: AI & LangChain in n8n

Module 5 Lesson 3: Agentic AI and Orchestration

Capstone Project: The Autonomous Market Analyst

Module 1 Lesson 1: Python and Virtual Environments

Module 1 Lesson 2: Installing LangChain

Module 1 Lesson 3: Installing Model Providers

Module 1 Lesson 4: API Keys and Environment Variables

Module 1 Lesson 5: First LangChain Run

Module 1 Wrap-up: Verification and First Call

Module 10 Lesson 1: Agent Fundamentals

Module 10 Lesson 2: The Agent Loop and Tool Selection

Module 10 Lesson 3: Safety Limits (Max Iterations & Timeouts)

Module 10 Wrap-up: Building Your First Agent

Module 11 Lesson 1: Why Structured Output Matters

Module 11 Lesson 2: Output Parsers (Pydantic & JSON)

Module 11 Wrap-up: Getting Reliable Data

Module 12 Lesson 1: Introduction to Callbacks

Module 12 Lesson 2: Implementing Callbacks in Chains

Module 12 Wrap-up: Inspecting the Machine

Module 13 Lesson 1: Debugging Chains

Module 13 Lesson 2: LangSmith Overview

Module 13 Wrap-up: Professional Observability

Module 14 Lesson 1: API Design with FastAPI

Module 14 Lesson 2: Caching and Retries

Module 14 Wrap-up: Shipping to Millions

Module 15 Lesson 1: Packaging LangChain Apps

Module 15 Lesson 2: Dockerizing LangChain

Module 15 Wrap-up: Your App on the Internet

Module 2 Lesson 1: What is a Model Abstraction?

Module 2 Lesson 3: Streaming Responses

Module 2 Lesson 4: Batching Requests

Module 2 Lesson 5: Provider-Agnostic Setup

Module 2 Wrap-up: Designing the Brain

Module 3 Lesson 1: Prompt Fundamentals

Module 3 Lesson 2: PromptTemplate (String Abstraction)

Module 3 Lesson 3: ChatPromptTemplate (Messaging Abstraction)

Module 3 Lesson 4: Few-Shot Prompting

Module 3 Wrap-up: Your Reusable Library

Module 4 Lesson 1: What are Chains?

Module 4 Lesson 2: Single-Step Chains (LCEL Basics)

Module 4 Wrap-up: Designing Complex Flows

Module 5 Lesson 1: Introduction to Document Loaders

Module 5 Lesson 2: PDF and Web Loaders

Module 5 Lesson 3: Text Splitters and Chunking

Module 5 Wrap-up: Processing Your Knowledge Base

Module 6 Lesson 1: What are Embeddings?

Module 6 Lesson 3: Introduction to Vector Stores

Module 6 Lesson 4: Similarity Search and k-Values

Module 6 Wrap-up: Storing Your AI's Memory

Module 7 Lesson 1: Why RAG Matters

Module 7 Lesson 2: The Retriever Interface

Module 7 Lesson 4: Designing RAG Prompts

Module 7 Wrap-up: Building a Q&A Bot

Module 8 Lesson 1: Why Memory is Needed

Module 8 Lesson 2: ConversationBufferMemory

Module 8 Lesson 3: Summary Memory

Module 8 Wrap-up: Conversations that Stick

Module 9 Lesson 1: What are Tools?

Module 9 Lesson 2: Defining Custom Tools (The @tool Decorator)

Module 9 Lesson 3: Built-in LangChain Tools

Module 9 Wrap-up: Giving Your Agent Powers

Module 11 Lesson 1: Side-by-Side Comparison

Module 11 Lesson 2: When to use LangChain

Module 4 Lesson 1: Agents in LangChain

Module 4 Lesson 2: Tool Definitions

Module 4 Lesson 3: Agent Executors

Module 4 Lesson 4: Memory Integration

Module 4 Lesson 6: Cost and Loop Control

Module 4 Wrap-up: Your First LangChain Agent

Module 6 Wrap-up: Migrating to the Graph

Module 8 Lesson 5: LangChain Integration