Choosing the Right Agentic Design Pattern: A Decision-Tree Approach

A structured decision-tree framework for selecting the right agentic AI design pattern. Five sequential questions guide developers through key task properties — whether the solution path is known, whether tool access is needed, whether task structure is articulable upfront, whether output quality outweighs speed, and whether specialization or scale demands multi-agent architecture. The framework maps to four destination patterns: Single Agent + ReAct, Planning Agent + ReAct, Single Agent + Reflection, and Multi-Agent Specialist System. Also covers common failure signals for each pattern and targeted fixes, such as switching from pure ReAct to planning when looping excessively, or refining critic setup when reflection cycles don't improve output quality.