Tree-of-Thought (ToT)
Tree-of-thought extends step-by-step reasoning by exploring multiple candidate paths, scoring them, and selecting the strongest solution.
Advanced Reasoning enhancement
When to use
Use it when the problem has several possible strategies, when creative exploration matters, or when a single reasoning path may get stuck.
Prompt example
Task: Apply Tree-of-Thought (ToT) to the user's request. Context: describe the input, constraints, target audience, and desired format. Instruction: be explicit, keep the output structured, and state any assumptions.
Output example
Structured answer based on the requested technique. Key result: the model follows the stated task and format. Notes: validate the output before using it in production.
Best practices
- Require multiple candidate approaches.
- Define scoring criteria before comparison.
- Ask the model to explain why a path wins.
- Limit the number of branches to control cost.
Common pitfalls
- Token consumption can grow quickly.
- Scoring can be subjective if criteria are vague.
- The first generated option may still receive unfair preference.