Tree of Thoughts is a reasoning approach where an AI model explores multiple possible solution paths in a structured, tree-like format before selecting the best outcome. Rather than committing to one line of reasoning and following it through, the model evaluates different branches and can backtrack when a path leads to a dead end.
It improves performance on complex tasks that require planning, exploration, and multi-step reasoning — where the first reasonable-looking path is not always the best one. For straightforward tasks, the overhead of exploring multiple branches is unnecessary. For tasks where the answer depends on finding the right sequence of decisions, ToT meaningfully improves reliability.
