Tree of thoughts prompting asks a model to produce several intermediate reasoning branches. Evaluating each branch or scoring them with a critic helps the LLM choose the most coherent final response.
This technique improves performance on complex tasks where single-step reasoning struggles. Tools can automate branch evaluation or allow humans to pick the best path.