thought-based-reasoning

Thought-Based Reasoning

Overview

Core principle: Making reasoning explicit improves accuracy 20-70% on complex tasks.

Instead of jumping to answers, decompose problems into steps. This catches errors, enables backtracking, and produces verifiable reasoning.

When to Use

digraph decide {
  "Problem type?" [shape=diamond];
  "Direct answer worked?" [shape=diamond];
  "Need confidence?" [shape=diamond];
  "Use direct prompting" [shape=box];
  "Use Zero-shot CoT" [shape=box];
  "Use Self-Consistency" [shape=box];
  "Use technique from table" [shape=box];

  "Problem type?" -> "Direct answer worked?" [label="simple"];
  "Problem type?" -> "Use technique from table" [label="math/logic/creative"];
  "Direct answer worked?" -> "Use direct prompting" [label="yes"];
  "Direct answer worked?" -> "Need confidence?" [label="no"];
  "Need confidence?" -> "Use Self-Consistency" [label="yes, high stakes"];
  "Need confidence?" -> "Use Zero-shot CoT" [label="no, just need better"];
}

Use when:

• Multi-step arithmetic or word problems
• Logic requiring deduction chains
• Decisions with multiple factors
• Creative problems needing exploration
• Any task where direct answer was wrong

Don't use when:

• Simple factual recall
• Single-step operations
• Time-critical responses where accuracy tradeoff acceptable

Quick Reference

Technique	Trigger	Template
Zero-shot CoT	Quick reasoning boost	"Let's think step by step..."
Self-Consistency	High-stakes decision	Run 3-5 paths, majority vote
Tree of Thoughts	Puzzle/creative block	Branch, evaluate, backtrack
Least-to-Most	Complex multi-part problem	Decompose → solve subproblems → combine
ReAct	Need external facts	Thought → Action → Observation loop
PAL	Math with computation	Generate code, execute it

Techniques

1. Zero-shot Chain-of-Thought

When: Quick prototype, no examples available