agent_learning
Agent Learning is a comprehensive, open-source roadmap and hands-on tutorial designed to teach AI Agent development from scratch. It guides users from foundational LLM concepts to building production-ready agent systems. The curriculum covers essential topics including Retrieval-Augmented Generation (RAG), memory architectures, tool use, function calling, agentic workflows, multi-agent collaboration, and agentic reinforcement learning. It provides in-depth technical coverage of key frameworks and standards such as LangChain, LangGraph, and the Model Context Protocol (MCP), alongside best practices for evaluation and deployment. A standout feature is its automated daily tracking of arXiv, which continuously integrates the latest research papers into the content to ensure the material remains at the cutting edge of the field. This resource is tailored for developers, students, researchers, and engineering teams who want to move beyond simple chatbot prompts to understand and construct sophisticated systems capa