Building Your First LangGraph Pipeline: A Decision-Makers Guide

▤ Summary

This article explains when LangGraph is the right choice for building production agentic AI workflows and when a simpler tool is better. It highlights the framework’s core strengths, including state management, checkpointing, and human-in-the-loop review. It also warns about common production failures such as state explosion, weak error handling, missing validation, and poor monitoring. The piece uses a real financial workflow example to show how maker-checker validation and human review can catch issues that basic testing misses. It ends with guidance on what to ask a LangGraph consultant before committing to an implementation.

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