LangChain Academy New Course: Deep Research with LangGraph

Course Overview - LangChain Academy launches "Deep Research with LangGraph" course, teaching users to build deep research agents from scratch [1] - The course focuses on multi-agent architecture and prompting techniques to improve performance and decision-making insights [2] - Participants will learn to build agents that interact with users, access tools, and manage multiple research agents [6] - The course emphasizes using LangSmith for observability and evaluation of agent components during development and deployment [5][7] Technological Focus - LangGraph, an agent orchestration framework, is highlighted for its suitability in building structured agentic applications [4] - The framework's built-in persistence layer is beneficial for tracking progress of multiple agents over extended periods [5] - Context engineering techniques are recommended to improve research results, such as focusing researchers on specific areas [3][4] Industry Application - Deep research is identified as a popular agent application, with major AI labs developing their own comprehensive report-generating products [2] - Companies are increasingly building their own deep research agents for use cases requiring high agency and decision-making [3] - The course aims to provide a working deep research agent adaptable to various user needs and use cases [7][8]