Tree of Thought
A prompting framework where the model explores multiple reasoning branches, evaluates intermediate states, and can backtrack from dead ends — like a deliberate tree search through thought space.
Why It Matters
Tree of Thought outperforms chain-of-thought on complex planning and reasoning tasks where the first approach tried may not be the best.
Example
Solving a puzzle by exploring branch A → dead end → backtrack → branch B → promising → continue → branch B2 → solution, rather than committing to one linear path.
Think of it like...
Like a chess player who considers multiple moves ahead, evaluates each position, and backs up when a line of play looks bad — exploring the tree of possibilities.
Related Terms
Chain-of-Thought
A prompting technique where the model is encouraged to show its step-by-step reasoning process before arriving at a final answer. This improves accuracy on complex reasoning tasks.
Reasoning
An AI model's ability to think logically, make inferences, draw conclusions, and solve problems that require multi-step thought. Reasoning goes beyond pattern matching to genuine logical analysis.
Planning
An AI agent's ability to break down complex goals into a sequence of steps and determine the best order of actions to accomplish a task. Planning involves reasoning about dependencies, priorities, and contingencies.
Prompt Engineering
The practice of designing and optimizing input prompts to get the best possible output from AI models. It involves crafting instructions, providing examples, and structuring queries to guide the model toward desired responses.