In this hands-on virtual workshop, you’ll learn how to design and build agentic retrieval-augmented generation (RAG) applications using LangGraph and MongoDB Atlas.
We’ll start with the basics: building a simple RAG flow powered by Atlas Vector Search. You’ll create a vector index in MongoDB Atlas to enable semantic retrieval. As the workshop progresses, you’ll gradually add more tools and complexity to your agent, including:
Conditional branching for dynamic workflows
Persistent memory with the MongoDB Checkpointer, storing agent state in Atlas
And more advanced multi-agent capabilities
By the end of the session, you’ll know how to combine retrieval, reasoning, and memory to build context-aware AI agents ready for real-world applications.
