Hello, Reddit!
At its core, Prompt Engineering is all about commanding the conversation with AI. Wanna write a poem, draft a project plan, or break down complex scientific terms? The right prompt can do that for you. If you want to learn more about Prompt Engineering feel free to join r/PromptWizards.
Let's dive into some Prompt Engineering concepts:
Let's start with the basics:
- Reductive operations: These yield responses that are smaller in size than the input prompt. Essentially, they distill information.
- Example: If the input prompt is a long article, and the task is to provide a summary, the operation used is reductive as the output (summary) is smaller than the input (the entire article).
- Transformational operations: These make sure the output maintains a relative balance with the input. In other words, the size of the response usually corresponds to the size of the input.
- Example: If the input is a text in English, and the task is to translate it into French, it employs a transformational operation as the output (translated text) is roughly the same size as the input (original text).
- Generative operations: These lead to outputs that are larger than the input. They take minimal information and build upon it to generate a detailed response.
- Example: If the prompt is a simple setting or a character description and the task is to write a short story based on it, this involves a generative operation because the output (the short story) is much larger than the input (the basic prompt).
Prompt Engineering is a multi-tiered process, progressing from fundamental questions to advanced "Tree of Thought" prompts, each with its own degree of complexity and objective. What seems like a simple AI-driven conversation is actually a dance of intricate operations, geared towards achieving the desired outcome or automating a task. Check this post to see the detailed tiers of prompts:
Walking the Fine Line: Hallucination vs Creativity It's crucial to distinguish reality from illusion. There's a fine line between hallucination (concocting entirely new contexts) and creativity (innovative applications of existing knowledge). The distinction catalyzes more effective prompt engineering while adding an extra shimmer to the AI magic.
Prompt Engineering Masterclass: The Real-Life Magic
The key to effective Prompt Engineering lies in patterns, this is just one of them, there is an infinity of them but I find this one to work really well, for those who are beginners this is supposed to be one single prompt and you basically adapt the structure to your use-case:
- Persona Instruction: (Act as... with X characteristic and Y style of writing and Z expertise)
- Task Instruction: (Your main and only task is to... while making sure that... and to...)
- Providing Output: Examples (Here are 3 examples of what I expect as an output...)
- Guideline to Execute: (use these examples in order to perform the task..., make sure to use examples wisely....to...and make sure...) Repeating such "make sure" etc is pretty useful to keep the output consistent.
- The Call To Action: Finally, a quick, concise reiteration of the task is needed. This gives the AI a final prod in the right direction. (Now take a deep breath, think step-by-step, and go on the main task and goal which is...)
This method, when used correctly, can produce astounding results, making AI a useful tool for complex tasks. Feel free to shoot any questions in the comments, or if you have any task automation that you are struggling with I can help!
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