Stop LLMs From Hallucinating: The Plan-and-Execute Pattern in LangGraph.js

Have you ever watched an AI agent spin its wheels, re-evaluating the same step over and over in an infinite reasoning loop? It’s a common frustration with autonomous systems. The agent has the tools, it has the context, but it gets stuck in a cycle of "Reason -> Act -> Observe -> Reason," often hallucinating new paths or forgetting its original objective. What if you could separate the thinking from the doing? Enter the Plan-and-Execute pattern. Unlike the dynamic but unpredictable ReAct (Reasoning and Acting) approach, Plan-and-Execute introduces a rigid separation of concerns. It decouples the strategy (the plan) from the tactics (the execution), creating deterministic workflows that are reliable, auditable, and efficient. In this guide, we’ll break down the architecture, compare it with ReAct, and provide a complete TypeScript implementation using LangGraph.js. The Core Concept: The Blueprint and the Builder To understand Plan-and-Execute, imagine constructing a complex mod