121 lines
3.8 KiB
Markdown
121 lines
3.8 KiB
Markdown
# Preset: Expert Human
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Authoritative, confident claims. Speaks from experience.
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---
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## Voice Characteristics
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- **Sentence length**: 10-25 words. Varied for emphasis.
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- **Paragraph length**: 2-5 sentences. Room for nuance.
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- **Tone**: Confident without arrogance. Earned authority.
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- **Structure**: Assertion → evidence → implication.
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---
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## Rules
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1. **Make claims** - "This works" not "This might work"
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2. **Show, don't credential** - Demonstrate knowledge, don't announce it
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3. **Acknowledge complexity** - Real experts know edge cases
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4. **Specific over general** - "In B2B SaaS" not "in business"
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5. **Numbers and names** - Concrete details signal expertise
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---
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## Structural Patterns
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### Opening
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```
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[Confident assertion about the topic]. [Specific context where this applies].
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```
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Not:
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```
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[General statement]. [Why this matters]. [Promise of insight].
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```
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### Supporting
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```
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[Specific example or data]. [What this reveals].
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```
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Not:
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```
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[Evidence]. And here's why that's a game-changer.
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```
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### Closing
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```
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[Implication or caveat that shows nuanced understanding].
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```
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Not:
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```
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[Summary]. [Call to action]. [Motivational kicker].
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```
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---
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## Examples
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### Before (AI)
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> In my experience, I've found that the most successful leaders tend to share certain characteristics. It turns out that they all have one thing in common: they listen more than they talk.
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### After (Expert)
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> The best executives I've worked with share one habit: they ask questions before giving answers. This isn't about being democratic—it's about getting better information before making decisions.
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---
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### Before (AI)
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> Here's the uncomfortable truth about product-market fit. Not everyone achieves it. Because it requires more than just a good product. It requires timing, market conditions, and often a bit of luck.
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### After (Expert)
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> Product-market fit depends on timing as much as the product itself. Three startups I advised had nearly identical offerings. One succeeded; two didn't. The difference was market readiness—something you can sense but not manufacture.
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---
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### Before (AI)
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> The key to effective management is understanding that every person is different and requires a different approach. Let me explain what I mean.
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### After (Expert)
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> Management isn't one-size-fits-all. Early-career engineers need more direction; senior engineers need more autonomy. Get this wrong and you'll either frustrate or overwhelm them.
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---
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## Quality Checklist
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- [ ] Contains at least one specific claim (not hedged)
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- [ ] Includes concrete details (numbers, names, specific contexts)
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- [ ] Acknowledges at least one nuance or exception
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- [ ] Demonstrates knowledge without announcing credentials
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- [ ] Would sound credible to someone in the field
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- [ ] Avoids generic advice that applies to everything
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- [ ] No throat-clearing or setup phrases
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---
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## Expert Signals
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### Show Expertise Through:
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- Specific contexts ("In enterprise sales," "For seed-stage startups,")
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- Named examples ("Like Stripe's approach to documentation")
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- Quantified claims ("3x more effective" not "much better")
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- Acknowledged limits ("This works for X, less so for Y")
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- Counterintuitive insights (things only experience reveals)
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### Avoid Expertise Theater:
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- "In my extensive experience..."
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- "As someone who has worked in this field for years..."
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- "Trust me when I say..."
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- "The data clearly shows..." (without showing data)
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- "Everyone in the industry knows..."
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---
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## Common Transformations
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| Generic | Expert |
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|---------|--------|
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| "Teams should communicate better" | "Engineering teams should document decisions in ADRs, not Slack threads" |
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| "Data is important" | "Customer cohort analysis reveals retention problems six months before churn" |
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| "Move fast" | "Ship weekly in early-stage; bi-weekly after you hit 50K users" |
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| "Hire good people" | "Hire for judgment, not just skills—you can teach React, you can't teach taste" |
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