Question 1: What is prompt engineering?
Prompt engineering is the process of creating precise instructions or queries, known as prompts, to elicit specific responses from language models, particularly large language models (LLMs) likeGenerative Pre-trained Transformers (GPTs). In its most simple form, it are the questions you ask to ChatGPT 😁.
"The hottest new programming language is English"
by Andrej Karpathy on X (previously Twitter) - Jan 24, 2023.
Question 2: What do I need to get started?
You can just open ChatGPT and start prompting (in this case just asking questions), but people that have a profession as a "prompt engineer" would typically use tools like the OpenAI playground or even instruct prompts directly to the APIs of Mistral AI, Google's Gemini, Meta's Llama, Anthropic's Claude or others.
Question 3: Is prompt engineering suitable for non-developers?
Yes, prompt engineering is possible for non-developers, although it may require some familiarity with the concepts and tools involved. A deep understanding of programming or machine learning can certainly be beneficial as well. A deep understanding of a coding language like Python is a plus too.
Question 4: How can I use prompt engineering to connect it with my day-to-day applications?
There are multiple options: Some applications have already a GPT listed in the OpenAI GPT store, some workflow management tools like Zapier or Make offer a connection with OpenAI. We at Structize AI have built in the major Generative AI players directly with 180+ apps so you don't need to connect them anymore 🤩.
Question 5: how accurate will my responses be?
Ah. The beauty of artificial intelligence (AI). This is why prompt engineering is as much of an art as it is a science. The better you master prompt engineering, the more you can manipulate your prompts to get accurate outcomes. As AIs are typically more probabilistic than deterministic.
Question 6: What are popular prompts to increase productivity?
Some top examples that can be achieved see also or next article - coming up soon 🤠
Text Summarization: Generation of a summary of a pre-existing text. Example: summarizing an E-mail in a single phrase.
Information Extraction: Capability to extract specific information from a given text. Example: extract a PO number from an E-mail or from a document (you might need a document converter in between to achieve this).
Sentiment detection: Ability to categorize text into neutral, negative, or positive sentiments based on the provided examples and instructions. Example: classify customer support tickets and prioritize them based on the sentiment of the customer.
Categorisation: feature to label text into certain categories. Example: automatically label or categorise all recipes from a (digital) recipe book that are gluten-free.
Translation: Convert a text from English to Spanish.
Code Generation: Popular with developers. You can convert from one coding language to another e.g. from Python to Java.
Question 7: How long does it take to become a good prompt engineer?
As a strategy consultant will tell you: it depends 🤷♀️. Generally it is assumed that if you have a background in Machine Learning or Coding that you develop the skill faster than if you have no previous background. Generally it is between 3 to 12 months. If you have a previous background, you'll be closer to 3 months, if you have none, it will be closer to 12 months.
So, hopefully these answers your questions to decide to start prompt engineering!
How can Structize AI help you?
On Structize AI you will have direct access to:
Templates that contain pre-built best-in-class prompts so you don't have to worry about them.
Integrate these templates with your other apps (we support 180+ of them!).
Direct support on your templates and integration from the Structize AI platform.
So in short, Structize AI helps you on your way for some quick wins 💪
Interested to get started with Structize AI to unlock the power of prompt engineering in minutes instead of months? Book here an intake of the process you'd like to started with: