Gemini & LangGraph: How to Build & Debug a Full-Stack Research AI Agent (Tutorial)

Dive into the gemini-fullstack-langgraph-quickstart, an incredible open-source Google project. This practical guide shows you how to build a powerful full-stack research-augmented AI agent capable of multi-step, iterative web research with citations, all powered by Google Gemini and LangGraph. Learn the project's React/FastAPI architecture, deep research capabilities, and tackle a real-world bug. This tutorial includes a step-by-step Docker setup, demonstrating how to use modern AI debugging tools like LangSmith for observability and an AI assistant for collaborative debugging to build and maintain sophisticated AI applications efficiently. Project Link: https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart Timestamps: 0:00 - Introducing the Gemini Deep Research Project 1:18 - Project Setup & First Run (Docker) 2:10 - Encountering a Bug 2:32 - Using LangSmith to Verify the Backend AI 3:18 - Collaborative Frontend Debugging with an AI Assistant 4:03 - The Fix in Action: Seeing the Full Research Process 4:55 - Final Thoughts & Key Takeaways Like, comment, and subscribe for more AI development tutorials!