Understanding how to create effective prompts is crucial to harness the full potential of ChatGPT. Even though the engine has improved a lot with the arrival of the GPT-4, there is still a need to know how to use it right. In this article, we will explore advanced prompt engineering techniques to improve the results. Let’s dive into eight techniques to help you master ChatGPT. I have used the pro-version of ChatGPT to try out these examples. But the same should also work with the free version of ChatGPT.
Few Shot Standard Prompts
Provide examples in your prompts to guide ChatGPT in producing the desired output. By including examples, you demonstrate the format or context you want the model to follow.
Assign roles to GPT-4 to receive targeted responses, as the model takes on the perspective or expertise of the assigned role.
Example: Act as a nutritionist and explain the benefits of a balanced diet.
Add Personality and Generate Knowledge
Customise the output by adding personality, style, and descriptors to your prompt. Generate knowledge before creating a final response for more detailed and well-supported answers. Sometimes you may have some knowledge in the form of an article or some list you may have found online. However, you can also use ChatGPT to generate the input knowledge.
Chain of Thought Prompting
Encourage GPT-4 to provide reasoning for its answers to improve accuracy and insight, particularly for tasks involving arithmetic, commonsense, and symbolic reasoning.
Use GPT-4 to refine the generated output iteratively by providing feedback on the initial response and asking the model to incorporate it in the next iteration.
Example: Initial prompt: Write a short summary of the advantages of electric cars. Generated response: Electric cars are eco-friendly and have lower operating costs.
Feedback: Expand on the advantages and mention how they contribute to a sustainable future. New prompt: Revise the summary to include more advantages of electric cars and explain how they contribute to a sustainable future.
Temperature and Top-k Settings
Control the randomness and creativity of the model’s output by adjusting the temperature and top-k settings. Lower temperature values produce more focused responses, while higher values generate more diverse and creative text. In the example below, I have selected – temperatures: 0.7 (for a more focused story) and 1.5 (for a more creative and diverse story). For a better explanation of these parameters, the advanced reader may want to read this article.
Include guiding phrases or constraints within your prompt to steer the model’s response in a specific direction.
Question Reformulation and Contextual Prompts
Rephrase questions or provide additional context to improve the quality of the response. Break complex questions into simpler queries for better answers.
Mastering prompt engineering techniques is a key to unlocking the full capabilities of GPT-4. By applying these eight methods, you can achieve better results and make the most of this powerful language model. Experiment with different techniques and combinations to find what works best for your specific use cases.