Prompt Engineering · Posted by Jason Park ·

The Role Prompting Technique: Make AI Act Like Any Expert

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Role prompting is probably the simplest technique that makes the biggest difference. Here’s how to use it effectively.

Basic pattern: “Act as a [specific expert role] with [years/type of experience] in [specific domain]. Your communication style is [description].”

Examples that work really well:

“Act as a senior product manager at a B2B SaaS company. You’ve shipped 15+ features and you focus on measurable outcomes. Review my PRD and give honest, actionable feedback.”

“Act as a board-certified nutritionist who specializes in sports nutrition. You give evidence-based advice and always cite relevant research. Help me design a meal plan for marathon training.”

“Act as a skeptical CTO evaluating a technology proposal. You care about scalability, maintenance cost, and team capability. Poke holes in my architecture design.”

Why it works: It constrains the model’s output to a specific knowledge domain and communication style, dramatically reducing generic responses.

Pro tip: Combine role prompting with a specific task format. “Act as X. Output your analysis in the format: [Strengths], [Weaknesses], [Recommendation with reasoning].”

What roles have you found most useful?

6 replies

6 Replies

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the skeptical CTO role is one i use constantly. adding 'assume the team is 3 devs and has no dedicated ops' makes it even more brutal and useful.

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one thing i figured out after way too many mediocre results - the role needs a POV, not just a title. 'UX researcher who believes most users never read instructions' hits different than just 'UX researcher'. the opinion is what shapes the output.

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the POV thing is underrated. 'senior SRE who has been paged at 3am for this exact failure mode' is way more specific than any job title alone.

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honest pushback: sometimes the role framing makes it too agreeable. 'act as a consultant' and suddenly everything is fixable. i get better results when i add 'you have seen this fail before and you are not optimistic.'

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does adding a pessimistic bias not just swing the output the other way though? like instead of generic optimism you get generic doom. genuinely curious if you've tested both.

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for anything legal or compliance related i always add 'you flag when something needs actual attorney review and you do not hedge every single sentence.' otherwise you get a wall of disclaimers that buries the actual answer.