LangChain v1.x Core Series
A 6-part developer's guide to mastering LangChain v1.x — from agent fundamentals and LangGraph stateful pipelines to RAG strategies, MCP decentralized integrations, production guardrails, and multi-agent supervisor systems.
Learning Path & Timeline
- Part 1•2026-06-11•Editorial
From Generative AI to Autonomous Agents (LangChain v1.x Core)
Understand the shift from static LLM calls to autonomous agents. Learn LangChain v1.x model patterns, message types, streaming, batching, and build your first runnable ReAct tool agent step by step.
- Part 2•2026-06-11•Editorial
Building Stateful Workflows & Graph Pipelines with LangGraph
Go beyond black-box agent loops. Learn how LangGraph models workflows as explicit graphs with typed state, conditional routing, multi-turn memory, and checkpointing — with step-by-step runnable code.
- Part 3•2026-06-11•Editorial
Enterprise Knowledge Retrieval: Traditional RAG vs. Vectorless RAG
Understand how RAG gives LLMs access to your private knowledge base. Compare the traditional vector pipeline against Vectorless RAG — with fully runnable examples, design trade-offs, and practical guidance on when to use each.
- Part 4•2026-06-11•Editorial
Deep Research Agents & Decentralized Integrations with MCP
Learn how deep research agents decompose complex tasks into sub-problems, and how the Model Context Protocol (MCP) lets agents connect to decentralized tool microservices — with full setup and runnable examples.
- Part 5•2026-06-11•Editorial
Production Engineering: Guardrails, Gateways, and AI Evaluation
Make your LangChain agents production-safe. Add input/output guardrails, LLM failover routing with LiteLLM, and measure quality with LangSmith evaluations — with complete runnable examples and design guidance.
- Part 6•2026-06-12•Editorial
Multi-Agent Systems: Supervisor Routing and Shared State Channels
Move beyond single-agent limitations. Learn how to build collaborative multi-agent systems in LangGraph where a supervisor routes tasks to specialised sub-agents over shared state channels — with fully runnable code and design guidance.