Here are some examples of different prompt strategies that can help you manage the output from the language model you are working with.
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Prompt Hacks
When prompting, you can use the following prompt hacks:
- "Do you understand the task?": End your prompt with this question. This way, you get the language model to repeat the described instructions, and you will discover if it has misunderstood the intention of your prompt.
- Format: Language models can deliver outputs in various formats. Therefore, consider how you want the output from your prompt. For example: In bullet points, as an email, table, or matrix.
- Tone: Do you want the language model to deliver in a formal or informal tone? Academic or humorous tone? Precise or poetic?
- Step-by-step: Asking the language model to deliver output in steps makes it better at following the progression of the conversation. Example: “Introduce yourself to the student and inquire about their (insert need/request). Wait for a response. Then ask which education they are pursuing and explain that the question helps tailor the academic level of your questions. Wait for a response and then inquire about…”
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Tips and Tricks for Prompting Images
When working with generating images in text-to-image models, it is important to be precise in your description of the desired image. Therefore, consider the following:
- Subjects/objects: Person, animal, thing, fantasy creatures.
- Interaction: How do the different elements interact with each other?
- Medium: Photography, painting, cartoon, sculpture, etc.
- Style: “In the style of…” Pop art, Dali, Disney, Alfred Hitchcock films, etc.
- Environment: Indoors/outdoors, desert, jungle, underwater, Gotham City, etc.
- Mood: Creepy, calm, feverish dream, energetic, etc.
- Perspective: Frog/bird's-eye view, close-up, POV, etc.
Copilot offers image generation with the same tool, DALL-E 3, found in ChatGPT 4. When using AI-generated images, it is good practice to mention it if you use them in assignments, presentations, or similar.
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Build an Advanced Prompt
Building a structured, advanced prompt is also known as prompt engineering. Prompt engineering is the art of fine-tuning and structuring requests to language models to optimize and target the generated responses to specific needs or goals.
Below is a template that illustrates the different elements of an advanced prompt: