For me, the Chain of Thought (CTO) is a specialized form of prompting that has a well-established role in the literature for enhancing reasoning capabilities in language models. Unlike regular prompting where the focus is generally on guiding the AI to a specific answer or type of response, CTO involves prompting the AI to articulate a step-by-step reasoning process. This not only makes the model’s thought process transparent but also simulates a more human-like way of solving complex problems by breaking them down into manageable parts. The ultimate goal of CTO is to enable AI to handle intricate queries more effectively by fostering deeper cognitive processes, thus bridging the gap between simple answer generation and true reasoning.