Expert-Principles Prompt Builder
Turn expert principles into precise AI editing guardrails
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 6
- Confidence
- 98%
This method begins by separating expert analysis from content generation. First, use AI to distill a respected practitioner's approach into clear guidelines. Move those guidelines between different models, asking each to make them more specific, understandable, punchy, and differentiated. A human then removes weak principles and strengthens the criteria that matter. The resulting principles become guardrails inside a role-and-task prompt. When content is supplied, the model must edit it and explain each change by reference to those guardrails. The mechanism works because AI is better at applying explicit criteria than independently discovering the subtle reasons an expert's work succeeds.
Origin
Extracted from Marketing Against The Grain
Core principles
- 01Extract the expert's principles before asking AI to imitate them
- 02Translate tacit expertise into explicit and understandable guardrails
- 03Use multiple models to expose weaknesses in each draft
- 04Keep human judgment in the refinement loop
- 05Require the model to explain its edits against the supplied principles
How to run it
- 1
Select the expert model
Choose a practitioner whose methods and standards are relevant to the output you need. Define whether the model should act as a writer, editor, strategist, or reviewer.
Pro tip Prefer an expert with a documented body of work and recognizable principles.
Watch out Fame alone does not make an expert's approach suitable for every task.
- 2
Distill the principles
Ask one AI model to translate the expert's approach into easy-to-understand operating guidelines. Focus on criteria that can actually guide an edit or decision.
Pro tip Frame the request as guidelines that could be handed to a working professional.
Watch out The first list will often contain generic best practices.
- 3
Cross-refine the guardrails
Give the first model's principles to a second model and ask it to improve their clarity, specificity, punch, and differentiation. Return the revision to the first model for another pass.
Pro tip Use models with different writing tendencies so their critiques are less redundant.
Watch out Do not assume model agreement proves that a principle is useful.
- 4
Apply human judgment
Remove principles that are unimportant or generic, retain those that capture the expert's distinctive method, and strengthen any weak wording.
Pro tip Ask whether each principle would change a real editing decision.
Watch out Skipping this step allows averaged, generic advice to dominate the prompt.
- 5
Build the operating prompt
Tell the model its role, task, expected output, and the principles it must follow. Include clear boundaries and the format in which edits should be returned.
Pro tip Request the original text, refined text, and reason side by side.
Watch out A long principle list without a concrete task can still produce unfocused output.
- 6
Audit the applied edits
Review whether the model followed the principles and require it to identify each change and justify it. Continue refining where its explanations remain generic.
Pro tip Use the explanations as a teaching aid for the human writer.
Watch out Do not treat a plausible explanation as proof that an edit is genuinely better.
In the wild
A marketer distills David Ogilvy's copywriting principles with two models, manually removes generic guidance, and places the remaining rules in an editing prompt. The prompt revises a LinkedIn post and returns the original line, refined line, and an explanation tied to clarity, consumer benefit, or appeal.
→ The marketer receives a more structured edit and can evaluate the reasoning behind each proposed change.
A sales team models a respected direct-response writer's documented principles, refines them across two models, and embeds them in a reviewer prompt. Every email is scored and revised against those explicit principles rather than a vague instruction to make it persuasive.
→ Reviews become more consistent, specific, and teachable across the team.
Common mistakes
Asking AI to discover greatness unaided
A model analyzing examples without supplied expertise tends to return broad advice that could describe almost any competent writing.
Keeping every generated principle
Unfiltered model output dilutes distinctive expert criteria with generic best practices.
Requesting edits without reasons
A rewritten draft alone does not show whether the model applied the intended principles or merely changed wording.
Is it for you?
Best for
Writers, editors, and marketers who can identify a proven expert model for the content they are creating.
Not ideal for
Tasks where the expert's principles are unknown, disputed, or impossible to translate into explicit criteria.
From the transcript
“But the first thing I did before I started to do this was to actually use AI to distill down those principles because I couldn't…”
“Then I would go back, right? So I go back and forth, and that's what I end up with a final list of these kind…”
“So I took out things that I didn't think were that important, I kept things in that I think were important, I refined things that…”
From the episode
Generate 10x Views On A LinkedIn Post With These GPT-4o Prompts