GPT-4 Prompt Engineering

In the video ‘5 Ways Your Prompts Need To Change To Get The Best’ by AI and Tech for Education, the presenter outlines five key tactics to improve prompt engineering for GPT-4. These tactics are based on OpenAI’s official prompt engineering guide and aim to help users get the best results from their prompts. The first tactic is to include specific and clear details in your prompt, which helps the model predict subsequent words more accurately. The second tactic is to split complex tasks into simpler subtasks, making it easier for GPT-4 to provide precise and helpful responses. The third tactic is to use larger prompts with delimiters, which allows for more detailed and complex interactions by clearly separating different parts of the request. The fourth tactic is to provide a reference text, useful for extracting specific information from a document. The fifth tactic is to provide examples using one-shot and few-shot prompting, which helps the model replicate the desired outcome by illustrating the task with clear examples. The video provides practical examples for each tactic, demonstrating how to implement them effectively. By following these strategies, users can enhance the quality and relevance of the outputs generated by GPT-4.