4-Day Series - Agentic AI with LangChain/LangGraph - Day 0

Source: Dev.to

Why this Series?

Large Language Models (LLMs) are powerful, but building reliable applications requires more than just a prompt. This series focuses on Agentic AI—systems that can reason, use tools, and make decisions to solve complex problems.

By the end of this course, you will understand how to:

• Move beyond simple linear chains to cyclic graphs.
• Build agents that can browse the web and interact with external APIs.
• Orchestrate multiple agents working together.
• Implement “human-in-the-loop” workflows for safety and control.

This is essential for developers looking to build production‑grade AI applications that are robust, stateful, and capable of autonomous action.

Prerequisites

• Node.js: Ensure you have Node.js installed (v18+ recommended).
• API Keys:
  • Create a .env file in the root directory (copy from .env.example).
  • Add your OPENAI_API_KEY.
  • (Optional) Add TAVILY_API_KEY if you want to use real search in Day 3 (code defaults to mock).

Installation

npm install

Agenda & Curriculum

This series is designed to take you from basic LLM interactions to building a production‑ready, human‑in‑the‑loop agentic workflow.

Day 1: Foundations (RAG)

• Concepts: Embeddings, Vector Stores, Retrieval Augmented Generation.
• Goal: Build a “Smart Reader” that can answer questions about your private data.

Run:

node day1-foundations/1-simple-chat.js
node day1-foundations/2-rag-chain.js

Day 1 details

Day 2: Intro to LangGraph (Agents)

• Concepts: StateGraphs, Nodes, Edges, Conditional Logic, Tools.
• Goal: Refactor the linear RAG chain into an autonomous agent that decides when to search.

Run:

node day2-langgraph/agent.js

Day 2 details

Day 3: Multi‑Agent Systems

• Concepts: Supervisor Pattern, Specialized Agents, Shared State.
• Goal: Orchestrate a team of agents (Researcher + Writer) to collaborate on a task.

Run:

node day3-multi-agent/team.js

Day 3 details

Day 4: Advanced Patterns (Persistence & Control)

• Concepts: Checkpointers (Memory), Interrupts, Human‑in‑the‑loop.
• Goal: Add “Time Travel” and Human Approval steps to make the agent safe for production.

Run:

node day4-advanced/human-loop.js

Day 4 details