In the era of generative AI, a company’s true AI capabilities go beyond just large data sets, advanced algorithms, and top engineers. It also involves knowing how and where to apply the technology, often with the help of non-technical experts deeply involved in the product development process. These experts can best identify the use cases for AI if they have a good understanding of AI.
Hi, I’m Sasha, a product manager at an AI startup by day and a developer of my own generative AI products by night. In this article, we’re going to explore the power of prompt engineering in AI and how it can help create consistent and predictable results, which are key to building great digital products.
Prompt engineering is the process of designing the input prompt for an AI model to guide its response. It involves structuring the prompt with clear instructions, providing relevant examples, specifying the desired output format, and even assigning a role persona to the AI model.
The instruction is the starting point of the prompt and should begin with an action verb to set a clear intent. For example, instead of asking the model to ‘generate a workout plan,’ a more specific instruction could be ‘create a personalized gym plan based on the user’s fitness level and time availability.’
Adding context to the prompt is crucial for getting tailored and individualized results. By providing information about the user, such as their fitness level and goals, the AI response can be more specific and relevant. For example, specifying Week 1, Day 1 of the workout plan and listing the exercises.
Examples in the prompt can further guide the AI by showing the desired response format. For example, using markdown to structure the plan with headers and lists for better readability. Output formatting is like the final touch of a recipe, guiding the AI on how the answer should appear. It can be as simple as specifying markdown format or suggesting a tone for the response.
Role persona is another element of prompt engineering that allows you to control the tone and style of the AI’s output. By assigning a specific persona, such as a personal fitness coach or a marketing guru, you can make the AI think and respond in a certain way.
Questioning the AI is also a part of prompt engineering. By asking the AI a question, you can guide its thinking and focus its response. However, it’s important to note that the AI’s knowledge is limited and may be outdated, so providing specific data for analysis is crucial.
In conclusion, prompt engineering is a powerful technique in AI that can greatly improve the quality and predictability of AI responses. By carefully designing the prompt with clear instructions, relevant examples, desired output format, role persona, and specific questions, you can guide the AI to generate consistent and tailored results. If you’re interested in learning more about prompt engineering, consider attending workshops tailored to your team’s needs and context.
Thank you for reading, and stay tuned for more articles on AI and prompt engineering!
