1. Check if conditions are fulfilled: Make sure your prompt contains what should be done if GPT is unable to do the task. An example would be "Respond with \"no steps provided"\ if there are no bullet points"
2. Few shot prompting: Giving the model a few example of what you want, a conversational style, or an explanation in the style of a professor goes a long way in making it give content you want.

A fundamental principle of CS applies here, GIGO. Garbage In, Garbage Out. If we give it the right info, it'll give us the right response.

GPT doesn't think like a human, but it does need to think in a colloquial sense. For the best responses, we need to give it time to reason and think.

By asking it to validate or sample an existing statement, it will understand and analyse it based on the POV that was presented in the text. But if you let the model understand it based on it's own terms and then ask it to infer, it'll give you a different POV altogether.

We can do this by applying the following tactics

1. Specify the steps: By specifying the exact steps needed, we get a much clearer output. An example would be to summarize a research paper, convert to french, list each heading out and convert it to a JSON object.
2. Instruct the model to figure out its own solution: Giving the model steps to do to get the output, and defining how you want the solution to be will give you your required output. An example would be to ask it solve a math problem by itself, and then compare it to a solution delimited by `` and check if it is true or not.