Master Prompt Engineering

In this module, you’ll learn about some effective prompt frameworks and how to make the most of Opal's capabilities using simple prompts right from the chat.

After completing this module you should be able to:

• Describe different AI prompt frameworks and their best use cases.
• Master prompt engineering to get your desired outcome.

AI prompt frameworks

Watch this video to get an introduction to prompt frameworks.

Now let's dive deep into each prompt framework discussed above.

RACE framework

CRISPE framework

COSTAR framework

CLEAR framework

KERNEL framework

Prompting fundamentals

In a nutshell, to make the most of Optimizely Opal, you need to communicate your requests clearly and effectively. Prompt engineering involves crafting precise prompts to get the best results. If you find the prompt frameworks overwhelming, here are a few key principles to keep in mind when crafting your prompts.

Key principles of effective prompting

• Clarity and specificity – Just like giving instructions to a human assistant, clarity and specificity are crucial for Opal Chat. Avoid vague or ambiguous language. The more precise you are with your request, the more accurate and relevant Optimizely Opal's response is.
  • Instead of – Tell me about marketing.
  • Try – Generate a list of content marketing strategies for e-commerce businesses targeting Gen Z.
• Context and background – Provide relevant context and background information to help Optimizely Opal understand your request better. This can include details about your target audience, campaign objectives, brand guidelines, or specific Optimizely functionalities you want to utilize.
  • Instead of – Create a campaign brief.
  • Try – Create a campaign brief for a new product launch targeting millennials, with a budget of $10,000, focusing on social media channels, and aligning with our brand's sustainability values.
• Desired output format – Specify the desired format for Optimizely Opal's response, such as a list, a paragraph, a table, or code. This information helps Optimizely Opal structure its output in a manner that is useful to you.
  • Instead of – Analyze our A/B test results.
  • Try – Analyze the A/B test results for the homepage banner, comparing variations A and B, and provide a table summarizing the click-through rate, conversion rate, and statistical significance for each variation.
• Iterative refinement – Do not expect the perfect response on the first try. Prompt engineering is an iterative process. Start with a general prompt, then refine it based on Optimizely Opal's initial response. Experiment with different phrasings, keywords, and levels of detail to fine-tune the output.
• Examples and demonstrations – Provide examples or demonstrations of the desired output to improve Optimizely Opal's understanding. You can refer to past campaigns, content pieces, or reports as templates for Optimizely Opal.
  • Instead of – Write a blog post about A/B testing.
  • Try – Write a blog post about A/B testing, similar in style and tone to the example provided in this link: [link to example blog post]. Focus on the benefits of A/B testing for Optimizely Experimentation users.