DAG ReAct

DAG ReAct is an agentic design pattern that structures the classic Reason-Act loop into a Directed Acyclic Graph to manage complex, multi-step task dependencies.

DAG ReAct evolves the standard ReAct (Reasoning and Acting) framework by organizing agent operations into a Directed Acyclic Graph (DAG) rather than a simple linear chain. While the original 2022 ReAct paper by Yao et al. introduced the concept of interleaving thought traces with tool actions, the DAG implementation allows for sophisticated parallel execution and explicit dependency mapping. By treating each thought-action-observation cycle as a node within a graph, developers can use orchestrators like LangGraph or LLMCompiler to execute independent subtasks simultaneously while ensuring sequential logic where required. This structure eliminates the local optimization traps of incremental decision-making, providing a clear execution path for high-stakes autonomous workflows in data engineering and complex problem-solving.

https://arxiv.org/abs/2210.03629