Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes
This paper is a practitioner guide to graph-based workflow pathways for long-running, stateful, multi-step generative AI systems in business processes. Rather than treating LangGraph, a low-level orchestration framework for stateful agents, as a model-quality benchmark target, we present three executable recipes -- SQL analytics with repair loops, agentic retrieval-augmented generation with evidence gating, and human-in-the-loop policy review with interrupt and checkpoint recovery -- to show how typed state, conditional routing, deterministic tools, retries, interrupts, checkpoints, and traces fit together. LangGraph is positioned by workflow-complexity fit, not as a universal default: si...
| Authors | Daniel Pearson, Sidney Shapiro, Emiliano Sebastian Gonzalez Venegas et al. |
|---|---|
| Primary category | cs.AI |
| Published | 21 July 2026 |
| Last updated at source | 21 July 2026 |
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