The five-section structure, real examples, the testing protocol, and the four mistakes that kill voice prompts before they get a chance. Three hours of focused work, output that sounds like you on first draft.
A voice prompt is a 500-800 word reference document with five sections: voice essence, mechanical rules, banned words, tone by context, signature moves. Built right, it produces 70-85% on-voice output on first draft. Built vaguely (which is most of the time), it produces output indistinguishable from default AI. The structure below is the difference.
The most common voice prompt looks like this: "Write in a friendly, professional tone. Be concise. Use a conversational style. Avoid jargon."
This produces nothing. The AI defaults to its baseline voice because the instruction is too vague to operationalise. "Friendly" means something different to every reader. "Concise" has no specification. "Conversational" describes a vibe, not a structure.
A voice prompt that actually works tells the AI specific, mechanical things it can match — sentence length ranges, banned words, signature sentence-opening patterns, tone shifts by format. Specificity is the difference. The five-section structure below is the framework that produces specificity reliably.
SECTION 1
One paragraph describing how this person communicates. Not adjectives — a description specific enough that someone reading it could write a sentence in the voice without ever seeing samples.
Bad: "Friendly, professional, approachable."
Good: "Talks like a smart friend who's done this before. Direct, specific, slightly opinionated. Uses short sentences for emphasis and longer ones for explanation. Names the reader's pain before naming the solution."
The good version gives the AI directional guidance. The bad version gives it nothing actionable.
SECTION 2
The quantifiable patterns the AI can mechanically reproduce. Use ranges (12-18 words) rather than absolutes (15 words) — real human voices vary deliberately for emphasis.
The eight rules to specify:
Specifying all eight produces consistent output. Specifying two or three produces inconsistent output that drifts back to default.
SECTION 3
15-30 specific phrases the writer would never use. The list closes the gap between "your voice" and "default AI vocabulary."
Common banned-word categories:
Add to this list quarterly as you spot AI defaults creeping into output. Treat it as a living document.
SECTION 4
The same voice should shift between formats — your email voice isn't your sales page voice isn't your social voice. Specify the shifts.
For each format the AI will write in, note: average warmth (formal to warm), urgency (none to high), specificity expected (high to very high), and any format-specific rules.
Example structure:
Email to clients: Warmer than other formats. First-person, conversational. Often opens with a personal observation before the business point. Closes with a question.
LinkedIn post: Direct. Hook in first line. 150-300 words. Specific numbers in body. No external links unless absolutely necessary.
Sales page: Sharper, more direct than other formats. Names objections explicitly. Specific outcomes with specific timelines.
Blog post: Most analytical of the formats. 1,500-2,500 words. Frameworks named explicitly. Section headings descriptive, not clever.
SECTION 5
The 3-5 distinctive habits that make the writing recognisably this writer. The fingerprints.
Three to five maximum — more than five dilutes the instruction and the AI starts treating signature moves as suggestions rather than rules.
Examples of common signature moves:
To identify your own: paste 10-20 samples into ChatGPT and ask "What are the three to five distinctive habits in this writing that an imitator would need to copy?" The answer is your signature moves.
Run 5-10 test prompts after building the voice prompt. Each tests a different content task:
Read each output. Apply this test sentence by sentence: would I actually write this?
If the answer is no for any sentence, identify which voice prompt rule failed and tighten it. Common failure modes:
Three iteration rounds is typical to get to 80%+ first-draft voice match. After that, the voice prompt is stable. Quarterly review thereafter is enough maintenance.
Mistake 1: Vagueness. "Friendly tone" produces default output. Specificity ("12-18 word sentences, always contractions, never semicolons") produces consistent output.
Mistake 2: Skipping the iteration step. The first version of the voice prompt is wrong. The second version is closer. The third version usually works. Don't expect first-build output to land — iterate.
Mistake 3: Never updating it. Voices evolve. Your business evolves. A voice prompt from 6 months ago might miss recent shifts. Quarterly review (15 minutes) is enough.
Mistake 4: Only using it for long-form. The voice prompt is most powerful when applied to everything — emails, captions, comments, ad copy. The more consistently you use it, the better the AI gets at approximating your voice on first draft.
DFY Voice System uses The Voice Build methodology — the same five-section structure above — executed for you in 2-3 working days. Voice prompt + custom GPT + hook library. £497 founder pricing.
See The Voice BuildA 500-800 word reference document describing how a person writes, fed into AI before any task to produce on-voice output.
500-800 words. Shorter is too vague; longer eats context window.
Being vague. "Friendly and professional" produces default output. Specificity ("12-18 word sentences, always contractions") produces consistent output.
Run 5-10 test prompts across different content tasks. Read each output sentence by sentence. Ask "would I write this?" If no, tighten the failed rule.
Copy the structure (five sections), not the content. Voice prompts are by definition specific to one writer.