LangGraph has introduced new templates in both Python and JavaScript to streamline the development and deployment of agentic applications, offering a balance between ease of use and customization. These templates, available through LangGraph Studio or as standalone GitHub repositories, allow developers to modify inner functionalities like prompts and chaining logic, providing fine-grained control over applications. Initially, three templates are being launched: a RAG Chatbot for data retrieval and response generation, a ReAct Agent for tool selection and task execution, and a Data Enrichment Agent for conducting research and verifying accuracy, with an additional empty template for custom builds. The templates are designed to be easily configurable and provider-agnostic, ensuring broad applicability and ease of debugging and deployment. LangGraph aims to expand its offerings over time, enhancing the flexibility and utility of its framework for orchestrating sophisticated agentic applications.