LangGraph introduces three innovative agent architectures—Plan-and-Execute, ReWOO, and LLMCompiler—that enhance the efficiency and effectiveness of language model-powered agents by adopting a "plan-and-execute" approach. These agents improve upon traditional Reasoning and Action (ReAct) agents by enabling faster multi-step workflows, reducing costs through fewer large language model calls, and enhancing task completion rates by explicitly planning all necessary steps. The Plan-and-Execute architecture separates planning from execution, allowing for efficient task completion without constant calls to large models. ReWOO introduces variable assignments in planning, allowing tasks to build on previous outputs without re-planning, although it still relies on sequential execution. LLMCompiler further optimizes speed by using a directed acyclic graph (DAG) to schedule and execute tasks in parallel, significantly reducing runtime and enhancing user experience. These architectures exemplify the plan-and-execute design pattern, offering notable advantages in applications that require multiple tool invocations or API calls, thereby minimizing the frequency of expensive model interactions.