Building Reliable AI Agents and LLM Apps Using LangChain and LangGraph
Association for Computing Machinery (ACM) via YouTube
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Learn to build production-ready AI applications and agents in this 55-minute conference talk featuring AI Engineer Mayo Oshin and Software Engineer Nuno Campos, moderated by Microsoft's Senior Developer Advocate Marlene Mhangami. Discover how LLM applications differ from traditional software through challenges like latency, unreliable inputs, and unpredictable outputs, then explore how LangChain—a popular development framework for large language model applications—addresses these unique challenges. Master LangGraph, an open-source AI agent framework specifically designed for building, deploying, and managing complex generative AI agent workflows that can reason and retrieve external data for enhanced context-awareness. Gain practical insights into developing reliable AI systems that can handle the inherent uncertainties of working with large language models while maintaining production-level reliability and performance.
Syllabus
Building Reliable AI Agents and LLM Apps Using LangChain and LangGraph
Taught by
Association for Computing Machinery (ACM)