Agentic Design Patterns with LangGraph

Author(s): Hamza Boulahia

Originally published on Towards AI.

Agentic Design Patterns with LangGraph

If there’s one thing I’ve learned building AI systems over the last couple of years, it’s this: patterns matter. Whether we’re designing traditional software or experimenting with large language model (LLM) agents, the way we structure workflows determines how robust, flexible, and scalable they’ll be.

The article discusses various agentic design patterns used in LangGraph for designing AI systems. It introduces concepts such as prompt chaining, routing, parallelization, and planning, emphasizing the importance of structured workflows in constructing efficient and scalable AI agents. Additionally, it explores multi-agent collaboration, showcasing how different specialized agents can work together to achieve complex tasks. The article integrates practical examples and code snippets to illustrate each design pattern effectively.

Read the full blog for free on Medium.

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Published via Towards AI