When it comes to AI, how good your prompt is can really make a difference in what you get back. The RISEN framework is a five-point recipe that turns fuzzy requests into laser-focused instructions: Role → Instructions → Steps → End goal → Narrowing. Developed by prompt educator Kyle Balmer, it’s quickly become a go-to structure for anyone who wants consistent, on-target output from models like ChatGPT, Claude, Gemini, and more.

RISEN

Best AI Results

Role

Tell the model who it is or what expertise it should assume. This sets tone, depth, and vocabulary. For example: “You are a veteran SaaS onboarding strategist”.

Instructions

State the core task in one direct sentence. Think “what” without the fluff. For example: “Outline a 4-week customer-onboarding plan for our HR/payroll platform.”

Steps

Break the task into an ordered checklist. Each step guides the model’s internal reasoning. For example: “(1) Identify key milestones, (2) assign owner roles, (3) list deliverables, (4) flag common risks”.

End Goal

Describe the finished artifact or success metric so the model knows when it’s “done.” For example: “Deliver a concise, board-ready plan under 600 words that the team can action immediately.”

Narrowing

Add constraints (scope, audience, style, length, exclusions). This keeps answers sharp and relevant. For example: “Focus only on Dynamics 365 Business Central integrations; ignore payroll legislation details”.

Putting it Together—Template & Live Sample

Role: Veteran SaaS onboarding strategist
Instructions: Outline a 4-week customer-onboarding plan for our HR/payroll platform.
Steps: (1) Identify milestones, (2) assign owner roles, (3) list deliverables, (4) flag common risks.
End goal: Produce a board-ready plan under 600 words.
Narrowing: Focus solely on Microsoft Dynamics 365 BC integrations; omit payroll legislation details.

Paste that into your favorite LLM and compare the output to a one-liner like “Give me an onboarding plan.” The RISEN-structured prompt delivers tighter, more actionable content almost every time.

Quick Evangelist Tips for RISEN Mastery

  1. Front-load context: Pack the Role and Instructions with industry or audience clues to reduce generic answers.
  2. Chunk complexity: Use Steps to force the model to reason methodically instead of hallucinating.
  3. Define “done”: A clear End goal minimizes rewrites.
  4. Fence the playground: Narrowing can be word-count limits, tonality (“friendly but professional”), or exclusions.
  5. Iterate openly: After the first draft, refine any RISEN element and resubmit—prompt engineering is a conversation, not a one-shot command.

Your Next Move

Grab the template, tweak each section for your use case, and watch the model’s outputs rise (pun intended) in clarity and value. Once you feel comfortable, experiment: replace “Narrowing” with “Novelty” to push creativity, or explore multiple Roles for perspective shifts. Happy prompting—and welcome to the AI evangelist club!

Conclusion

The RISEN framework is a game-changer for creating clear, actionable prompts that deliver great results. By focusing on clarity, structure, and specifics, it turns vague ideas into sharp, focused outputs that save time and cut down on confusion. Fine-tuning your prompts is all part of the process, so treat it like a conversation—adjust, refine, and see how much better your results can get. Give it a shot and watch your AI collaboration reach new heights!

Interested in learning more about implementing AI at your organization? Check out our free eBook “8 Keys to Success with AI & Microsoft Copilot” where we share best practices and strategy for deploying Copilot based on firsthand experience.

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