LangGraph has emerged as a promising framework for building AI agents, favored by companies like Replit, Klarna, LinkedIn, and Uber, due to its low-level approach that eschews hidden prompts and enforced cognitive architectures, making it production-ready and distinct from other frameworks. While acknowledging the benefits of higher-level abstractions for ease of use and experimentation, LangGraph has introduced prebuilt agents to balance accessibility with flexibility. These agents, packaged separately in LangGraph 0.3, include Trustcall for structured extraction, LangGraph Supervisor for multi-agent architecture, LangMem for long-term memory, and LangGraph Swarm for swarm architecture, all available in Python and JavaScript. This initiative aims to stimulate a community-driven collection of prebuilt agents, with guidelines provided for developers to create and register their own packages, drawing inspiration from the successful integration model of LangChain, which boasts over 700 community-maintained integrations.