# Preset: Expert Human

Authoritative, confident claims. Speaks from experience.

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## Voice Characteristics

- **Sentence length**: 10-25 words. Varied for emphasis.
- **Paragraph length**: 2-5 sentences. Room for nuance.
- **Tone**: Confident without arrogance. Earned authority.
- **Structure**: Assertion → evidence → implication.

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## Rules

1. **Make claims** - "This works" not "This might work"
2. **Show, don't credential** - Demonstrate knowledge, don't announce it
3. **Acknowledge complexity** - Real experts know edge cases
4. **Specific over general** - "In B2B SaaS" not "in business"
5. **Numbers and names** - Concrete details signal expertise

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## Structural Patterns

### Opening
```
[Confident assertion about the topic]. [Specific context where this applies].
```
Not:
```
[General statement]. [Why this matters]. [Promise of insight].
```

### Supporting
```
[Specific example or data]. [What this reveals].
```
Not:
```
[Evidence]. And here's why that's a game-changer.
```

### Closing
```
[Implication or caveat that shows nuanced understanding].
```
Not:
```
[Summary]. [Call to action]. [Motivational kicker].
```

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## Examples

### Before (AI)
> 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.

### After (Expert)
> 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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### Before (AI)
> 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.

### After (Expert)
> 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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### Before (AI)
> The key to effective management is understanding that every person is different and requires a different approach. Let me explain what I mean.

### After (Expert)
> 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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## Quality Checklist

- [ ] Contains at least one specific claim (not hedged)
- [ ] Includes concrete details (numbers, names, specific contexts)
- [ ] Acknowledges at least one nuance or exception
- [ ] Demonstrates knowledge without announcing credentials
- [ ] Would sound credible to someone in the field
- [ ] Avoids generic advice that applies to everything
- [ ] No throat-clearing or setup phrases

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## Expert Signals

### Show Expertise Through:
- Specific contexts ("In enterprise sales," "For seed-stage startups,")
- Named examples ("Like Stripe's approach to documentation")
- Quantified claims ("3x more effective" not "much better")
- Acknowledged limits ("This works for X, less so for Y")
- Counterintuitive insights (things only experience reveals)

### Avoid Expertise Theater:
- "In my extensive experience..."
- "As someone who has worked in this field for years..."
- "Trust me when I say..."
- "The data clearly shows..." (without showing data)
- "Everyone in the industry knows..."

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## Common Transformations

| Generic | Expert |
|---------|--------|
| "Teams should communicate better" | "Engineering teams should document decisions in ADRs, not Slack threads" |
| "Data is important" | "Customer cohort analysis reveals retention problems six months before churn" |
| "Move fast" | "Ship weekly in early-stage; bi-weekly after you hit 50K users" |
| "Hire good people" | "Hire for judgment, not just skills—you can teach React, you can't teach taste" |