What is Chain-of-Thought
A way to describe intermediate steps in solving a problem to improve the testability and controllability of the answer.
Definition
Chain-of-Thought is a way of describing intermediate steps in solving a problem in order to improve the verifiability and controllability of the answer. Simply put, this concept helps you better use AI tools and understand their limitations. In practice, it helps to understand what capabilities the tool actually has, what data it will need, and what limitations are worth checking before implementation.
Example
The user asks the assistant not just to give a summary, but to show a short explanation on what grounds he chose the option.
Why it matters
Understanding this term helps you better ask complex questions of AI and check the progress of the solution. This helps you choose AI tools not by big promises, but by how they work in a real problem.
How it works
The user sets the goal, clarifies the context, verifies the answer, and, if necessary, limits or reformulates the request. In the case of the term “Chain of Reasoning”, it is important to look separately at the data, quality criteria and application conditions.
Where it is used
- Useful for anyone who writes queries, works with chatbots, assistants and content generators.
Limitations
User concepts can easily be simplified into myths, so it is important to show practical examples and real-world limitations.