Reasoning patterns
Definition
Reasoning patterns are structured ways to elicit or organize model reasoning: chain-of-thought (step-by-step), tree-of-thoughts (explore branches), ReAct (reason + act), and RDD (retrieval-decision-design), among others. Using a clear pattern improves reliability (more consistent reasoning) and debuggability (you can inspect steps or actions).
They are used in prompt engineering (e.g. CoT) and inside agents (e.g. ReAct, RDD). Choosing a pattern depends on the task: CoT for math/reasoning, ReAct for tool use, ToT for search/planning, RDD for spec compliance.
How it works
You feed input (question, task) into a pattern: the pattern constrains how the model reasons or acts (e.g. “think step by step”, or thought–action–observation loops). The model produces an output (answer, action sequence). Prompts or system design encourage the model to show reasoning (e.g. “Think step by step”) or to interleave thought and action. Patterns can be combined (e.g. CoT inside an agent loop). See the linked pages for each pattern’s details.
Use cases
Different patterns suit different needs: CoT for stepwise reasoning, ReAct for tool use, ToT for search and planning.
- CoT: math, logic, and multi-step reasoning tasks
- ReAct: tool-using agents that reason before each action
- ToT: search and planning over multiple solution branches
External documentation
- Chain-of-Thought Prompting (Wei et al.) — CoT paper
- ReAct: Synergizing Reasoning and Acting (Yao et al.) — ReAct paper
- Tree of Thoughts (Yao et al.) — ToT paper