AI Agent Architectures: How to Choose the Right Pattern for Your System There is no single best AI agent architecture. A ReAct agent may be ideal for a tool-using support assistant, while a Plan-and-Execute workflow is better for a multi-step business process, and a Deep Research agent is designed for broad investigation across many sources. The right choice depends on task complexity, tool risk, latency, cost, reliability, and the level of autonomy you can safely allow. This guide compares six widely used agent patterns: Reflect, ReAct, Plan-and-Execute, Query Decomposition, Reflexion, and Deep Research. It explains how they work, what they solve, their trade-offs, and where each fits in production system design. Press enter or click to view image in full size Generated by AI What Is an AI Agent Architecture? An AI agent architecture defines how a language model decides, acts, observes results, uses tools, stores memory, checks its own work, and returns an answer. A standard LLM appli...