Production AI Agents with LangChain + LangGraph [2026]

Engineered for intermediate Python developers and software engineers, this comprehensive course by Paulo Dichone bridges the gap between basic LLM scripting and production-ready cognitive architecture. Students dive deep into the ecosystem of LangChain and LangGraph to build resilient, stateful AI agents that can handle complex, real-world tasks. The curriculum meticulously unpacks LangChain Expression Language (LCEL) for composable chains, before transitioning into LangGraph to construct state machines with cyclical graphs, conditional routing, and crucial human-in-the-loop validation patterns. Beyond basic agentic workflows, the course emphasizes enterprise-grade practices, including advanced Retrieval-Augmented Generation (RAG) pipelines, multi-agent coordination frameworks, and robust security protocols to prevent prompt injection. By integrating FastAPI, Docker, and LangSmith for real-time tracing and evaluation, learners acquire the precise skillset needed to design, secure, test, and deploy multi-agent systems at scale. Whether you are building a self-correcting code reviewer or an automated customer support matrix, this course provides the blueprint for launching enterprise-grade AI applications with measurable business value.