Ever wonder why AI sometimes misses the mark?
Most of the time, it’s because the instructions aren’t clear enough.

Enter ROSES Prompt Theory—a simple yet powerful 5-step framework that helps you create prompts that get you accurate, relevant, and high-quality results from AI tools like ChatGPT, Claude, or Gemini.

In this guide, we’ll cover what ROSES is, where it comes from, why it works, and how to apply it across AI, education, content, and business—with practical tips, comparisons, and examples.

What is ROSES Prompt Theory?

ROSES stands for:

• R – Role
• O – Objective
• S – Steps
• E – Expectations
• S – Style

It’s a structured prompt design method that breaks your request into clear, context-rich parts.
When you tell AI who to be, what to do, how to do it, what success looks like, and in what tone or format, you drastically improve its output quality.

Example:

Role: “You are a social media strategist.”
Objective: “Create a 30-day Instagram content plan for a tech blog.”
Steps: “1. Identify audience; 2. Plan daily posts; 3. Suggest captions and hashtags.”
Expectations: “Actionable, beginner-friendly, and trending ideas.”
Style: “Friendly, engaging, and data-backed.”

Why Does ROSES Work?

AI performs best when you reduce ambiguity.
ROSES uses proven principles from cognitive load theory and instructional design:

• Breaking tasks into steps reduces confusion.
• Clear roles and objectives give the AI context.
• Specifying style and expectations ensures outputs match your goals.

In short, ROSES guides the AI’s “thinking process” to deliver focused, high-quality results.

The 5 Components of ROSES

1. Role – Who should the AI be?

Defining a role sets perspective and expertise.
Examples:

• “Act as an experienced UX designer.”
• “You’re a financial advisor specializing in investments.”

2. Objective – What do you want?

State your goal in one clear sentence.

• Bad: “Write something about AI.”
• Good: “Explain machine learning for beginners in simple, non-technical language.”

3. Steps – How should it get there?

Guide the AI with a logical plan.

• “First, summarize the topic. Then provide 3 real-world examples. Finally, create a pros-and-cons table.”

4. Expectations – What defines success?

Set the standard for the output—length, tone, and must-have elements.

• “Use simple language, about 600 words, include headings, and finish with a call-to-action.”

5. Style – How should it sound?

Pick the tone and voice that fit your audience.

• Friendly and conversational.
• Formal, academic, or data-driven.

Origins of ROSES

ROSES emerged from the AI prompt-engineering community in the early 2020s.
Experts like Shelly Palmer and Fabio Vivas popularized it as a practical framework for crafting effective prompts.
Though not an academic theory, it draws from communication and learning science, emphasizing clarity, context, and structure.

Where Can You Use ROSES?

AI Prompt Engineering

Use ROSES for complex tasks:

• “Role: SEO expert; Objective: create a keyword plan; Steps: analyze competitors, select long-tail keywords, draft content outline; Style: professional and data-backed.”

Education

Teachers can use ROSES to design AI tutoring prompts:

• “Role: math tutor; Objective: teach quadratic equations; Steps: explain concept, show examples, provide practice problems; Style: simple and friendly.”

Content Writing and Marketing

Ensure AI matches your brand voice:

• “Role: brand copywriter; Objective: craft a product launch email; Expectations: clear CTA, emotional hook; Style: engaging and on-brand.”

Business Communication

Draft plans and strategies with precision:

• “Role: crisis manager; Objective: stabilize operations after supply chain disruption; Steps: assess risks, propose backup plans, communicate updates.”

ROSES vs. Other Prompt Frameworks

• SCQA (Situation, Complication, Question, Answer): Great for storytelling, but less action-oriented than ROSES.
• CRAFT (Context, Role, Action, Format, Target): Similar structure, but lacks ROSES’s focus on Steps and Expected outcomes.
• RACI (Responsible, Accountable, Consulted, Informed): Assigns roles in projects, not in AI prompts.

Bottom line: ROSES is your go-to when you need structured, detailed, and goal-oriented prompts.

Advantages and Limitations

Advantages:

• Produces clear, relevant, and actionable AI outputs.
• Reduces back-and-forth revisions.
• Works across multiple industries and use cases.

Limitations:

• Takes extra time to craft full prompts.
• May limit AI’s creativity if instructions are too strict.

Example: ROSES in Action

Prompt:
“You are an experienced HR consultant (R). Create a plan to improve employee retention by 15% in 6 months (O). Analyze survey data, identify churn risks, propose retention programs, and give a timeline (S). Output must be practical, data-driven, and easy to implement (E). Write in a professional, consulting-style format (S).”

Output:
A clear, step-by-step retention strategy with actionable steps and timelines.

Pro Tips for Using ROSES

• Add examples of desired output.
• Iterate—refine prompts if results aren’t perfect.
• Use constraints (e.g., word count, style) for more control.
• Combine with SCQA or CRAFT for storytelling or audience-focused tasks.

Conclusion

ROSES Prompt Theory is more than a buzzword—it’s your blueprint for communicating with AI effectively.
By defining Role, Objective, Steps, Expectations, and Style, you’ll save time, reduce frustration, and consistently get precise, high-quality outputs.

Whether you’re an educator, marketer, business leader, or AI enthusiast, ROSES will help you unlock the true potential of AI.