Best of langgraph — August 2025
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Auth0·38w
How to build an AI Assistant with LangGraph and Next.js
A comprehensive guide to building a production-ready AI assistant using LangGraph Server and Next.js. The tutorial covers migrating from Vercel AI SDK to LangGraph Server, implementing step-up authorization with Auth0 for secure API access, and integrating multiple tools including Google Calendar and custom APIs. Key features include handling authorization interrupts, streaming responses, and creating a scalable architecture for AI agents that can access external services securely.
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NVIDIA Developer·34w
How to Scale Your LangGraph Agents in Production From A Single User to 1,000 Coworkers
NVIDIA shares their approach to scaling LangGraph AI agents from single-user prototypes to production systems supporting 1,000+ concurrent users. The process involves three key steps: profiling single-user performance to identify bottlenecks, conducting load tests to estimate hardware requirements, and implementing monitoring during phased rollouts. Using the NeMo Agent Toolkit, they deployed an internal AI-Q research agent, discovering critical issues like CPU misconfiguration and timeout handling that only emerged under load. The methodology includes evaluation tools, sizing calculators, and OpenTelemetry integration for comprehensive observability.
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Towards Data Science·36w
LangGraph 101: Let’s Build A Deep Research Agent
A comprehensive tutorial on building AI research agents using LangGraph, Google's open-source framework. Covers core concepts including graph-based workflow modeling with nodes and edges, state management for agent memory, structured outputs for reliable LLM responses, tool calling for web searches, conditional routing for decision-making, and parallel processing for concurrent operations. Uses Google's Deep Research Agent implementation as a practical example, demonstrating how to create agents that can autonomously search the web, evaluate results, and generate comprehensive reports with citations.
