Effective Prompt Structures & Frameworks

In this lesson, you will learn the RTF (Role-Task-Format) framework, a simple yet powerful tool for effective communication with AI. You will get to know its components and practical examples, and learn how to use it to simplify everyday text-based tasks.

This lesson shows you how to use the RTF (Role, Task, Format) framework to get not only textual but also structured results, such as tables. You will learn how important the Format component is for integrating AI's response into your workflow and saving time.

In this lesson, you will learn the CO-STAR prompt framework, a powerful tool for communicating with AI that is especially effective for creating texts where audience, style, and tone play a decisive role. You will get to know its components and apply them in practice using the example of a LinkedIn post.

This lesson shows you how to use the CO-STAR framework to draft an effective sales proposal outline after a sales call. You will learn how to incorporate client context into a prompt so that AI returns text tailored to the specific conversation rather than generic content.

In this lesson, you will learn the CRISPE framework, an advanced approach to communicating with AI that allows you to obtain not just text, but logically structured workflows and multifaceted analysis. You will get to know each component (Capacity, Role, Insight, Statement, Personality, Experiment) and learn its practical application through the example of a brief market analysis.

In this lesson, you will learn how to use the CRISPE framework for in-depth analysis of long documents with the help of AI. We will discuss why simple summarization is ineffective and how CRISPE helps extract targeted, decision-relevant information.

In this lesson, you will learn how to choose the right AI prompt framework (RTF, CO-STAR, CRISPE) based on the type of task. You will create a practical "selection card" that will help you optimize your communication with AI and avoid random prompting mistakes.

This lesson explores how to combine the strengths of different AI prompt frameworks to create more complex and effective instructions for real-world work tasks. You will learn when and how to use one framework as the primary structure while adding elements from another to optimize the result.

In this lesson, you will learn how to evaluate your prompts in order to get stable, repeatable, and high-quality results from AI. We will go over a practical checklist that will help you turn your prompt engineering skills from a "one-off attempt" into a systematic approach.