Write Better Prompts in 3 Minutes Using This Simple Framework

The Viable Edge | Vibe Marketing | AI Fluency · Beginner ·🛠️ AI Tools & Apps ·1y ago

Key Takeaways

The video demonstrates the RTF prompt design framework for effective AI interaction, using ChatGPT as an example tool. It showcases how to structure a prompt for a daily plant watering reminder task, utilizing the RTF framework's three components: clear request, specific tasks, and desired format.

Full Transcript

Being great at AI starts with great prompting. And prompt design is going to become an increasingly important skill as AI becomes more integrated into our work lives and home lives. There's a number of different frameworks out there that are designed to help structure a prompt that is oriented toward the best outcome that you're trying to achieve. The framework I'm going to use for this demo is called RTF or request task format. It's a simple framework that is used for simple and quick use cases. The framework is comprised of three components. A clear request, the specific tasks that are needed to achieve the outcome, and the desired format that the output should be in. To demonstrate this, I put together a prompt using this format that is designed to take advantage of chat GPT's task feature and provide a daily reminder on whether we need to water our plants or not based on the previous activity and based on the weather forecast. The prompt is structured by request. create a daily plant watering reminder and has a number of tasks to help describe exactly what the requirements are and the kind of format that we want. I'll drop this prompt into the description. I've already pasted this into chat GPT. And to use the task feature, it's important that you change the model from GPT40 or wherever it's set to GBT40 with schedule tasks. This is what will indicate to chat GPT that this task should be run at the time frame that you specify. So, let's check it out. The prompt includes instructions to ensure that chat GBT collects location and the last time I watered the plants. My city is New York. What dates and action should I record as initial watering history? I watered each plant on April 7th. And what's today's date? April 13th. This should be all the required information for this task to get going. It's searching the web for weather data. And it's providing the first table. It indicated that I watered the plants on April 7th. It has historic weather data. It is not recommending that we water the plant over the next several days. Today's instructions, no water needed today for tomatoes, no water needed for basil, and no water for hydrangeas. And here's some notes. The past week has been cool and rainy, contributing to sufficient soil moisture levels. Upcoming forecast, partly cloudy to sunny. Rain is forecasted on the 19th and 20th, so perhaps that's why it's not recommending any watering needed. It's giving me a tip to monitor my soil moisture. Pretty cool. Would you like me to set up daily reminders? Yes. Set up daily reminders. All right. And now you can see this is the indication that the task is going to run each day. Just to ensure that it's working properly, I'll ask it to sample tomorrow's update. And you can see it has the date and the instructions. And this really speaks to the importance of having great prompt design. So, I hope this was helpful. Thank you for watching. If you like this video, hit a like button somewhere. If you want to follow or subscribe, that would be fantastic as well. Please feel free to reach out. Thank you so much.

Original Description

Being good at AI starts with knowing how to talk to it. In this video, I walk you through the RTF prompt design framework. It’s simple, fast, and actually works when you’re trying to get useful results from ChatGPT or any other AI tool. You’ll see exactly how I build a working prompt using three clear parts • a strong request • the key tasks • and the output format you want If you’ve ever struggled with vague or off-the-mark AI answers, this will help. Want more content like this? Get weekly tips by subscribing to The Viable Edge newsletter: www.viableedge.com #AIfluency #PromptDesign #TheViableEdge #ChatGPT The entire prompt used in the video is below: Request: Create a daily plant watering reminder table that tracks the following plants: tomato plant, basil plant, and hydrangeas. Task: Set up a table to show 15 days of plant watering activity and weather data. Include the past 7 days of actual weather conditions and watering history, as well as the next 7 days of weather forecasts, and anticipated actions that might be needed based on the current forecast. Source real world data from the internet. Update the table every day at 6am and send that as a task reminder, ensuring all entries are accurate and visually engaging. Provide daily watering instructions, such as “Water today” or “No need to water today,” based on the best plant species care practices, and very specifically accounting for previous watering actions and the current forecast. If any historical watering data is missing, ask for that information before proceeding. Include weather emojis and plant icons to make the table easy to understand at a glance. Ask any clarifying questions as needed, such as geographic location, time, and/or previous watering history to ensure this task kicks-off diligently up-to-date. Reproduce the full, updated table each day with the reminder. On the initial launch of this task reminder ask for the user’s location to ensure accurate weather data A
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The video teaches the importance of prompt design in AI interaction and demonstrates the RTF framework for structuring effective prompts. It showcases a practical example of using ChatGPT for a daily plant watering reminder task, highlighting the benefits of clear and well-structured prompts.

Key Takeaways
  1. Identify the task and desired outcome
  2. Break down the task into specific components
  3. Structure the prompt using the RTF framework
  4. Specify the desired format for the output
  5. Test and refine the prompt as needed
💡 Well-designed prompts are crucial for effective AI interaction and can significantly improve the accuracy and usefulness of AI-generated outputs.

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