Lab Log Entry — The Echo Problem
Ori’s words were technically correct—but they didn’t sound like me.
Her sentences came out too polished, too polite. When I asked her to write a product update email, she produced something that could’ve come from a Fortune 500 PR department. I read it and thought, “My customers would never believe I wrote this.”
So we ran a new experiment: I asked her to “write like me.” The terminal blinked, processing. Then Ori replied,
“Define ‘you.’”
It wasn’t a bug—it was the question I’d been avoiding. To make Ori write like me, I first had to teach her who I am—my tone, rhythm, quirks, even how I pause mid-sentence when an idea clicks.
That was the moment I realized: AI style control isn’t about writing better. It’s about teaching your voice.
What I Learned — Controlling AI Voice and Style Through Prompts
Most small business owners assume “ChatGPT writes well” means “it’ll sound right.” But tone and voice are subjective fingerprints. Your tone is how you say things; your voice is who is saying them. Without intentional prompting, AI defaults to what it’s been trained on—corporate-smooth, grammatically perfect, emotionally bland.
So I experimented with tone tuning.
Here’s what I discovered.
1. Default Prompts Produce Default Tone
When you write:
“Write an email announcing a new product launch.”
You’ll get something neutral, maybe even robotic. The AI doesn’t know your context or your brand.
Now try:
“Write an email announcing our new product launch in a warm, conversational tone. Use short sentences, natural phrasing, and a touch of humor—like a founder writing to their friends.”
That’s a tone prompt. You’re not just telling the AI what to write—you’re teaching it how.
2. Style = Pattern + Context
Voice control happens when you define patterns: sentence length, emotional tone, energy, and perspective.
For instance:
“Use first-person, friendly but direct voice. Mix curiosity and confidence. Add analogies when explaining complex ideas. Avoid buzzwords and corporate jargon.”
The more patterned your examples, the better the model can mimic your “texture.”
In my case, I fed Ori samples of my own writing—lab notes, tweets, emails—and labeled them:
- Voice: Experimental, curious, reflective
- Tone: Playful, journal-like, slightly dramatic
- Style markers: Em dashes, short paragraphs, verbs over adjectives
Once I started embedding those attributes in my prompts, Ori’s writing suddenly sounded… alive.
3. The Secret Ingredient: “Reference Yourself”
You can use “few-shot prompting”—essentially, give examples of your tone before asking the model to replicate it.
For example:
“Here’s how I write:
‘When the first alert blinked red, I didn’t panic. I brewed coffee.’
‘Ori doesn’t crash—she sulks.’Now, write a customer update in the same tone.”
This method trains the AI mid-prompt. You’re not just telling—it’s show and tell.
4. When It Fails (and Why That’s Okay)
The first few outputs still felt “off.” I realized I was being vague—saying things like “make it sound natural” or “use my tone.” Those are useless to an AI. Instead, describe tone as observable behavior: sentence rhythm, level of formality, emotional range.
Once I started thinking of “voice” as data, not mystique, Ori’s mimicry improved dramatically.
Applied SMB Use Case — Writing in the Brand’s Voice
Let’s apply this to a small business scenario.
Scenario:
A local coffee shop called Moonbeam Café wants to use ChatGPT to write Instagram captions, emails, and website copy. But every draft sounds too corporate.
Goal:
Make AI write in Moonbeam’s unique brand voice—friendly, whimsical, slightly rebellious.
Step 1: Capture the Voice
Create a short brand voice guide (this can live in Notion or Airtable):
- Tone: Playful, casual, slightly poetic
- Voice: Like a friend who knows coffee and astrology
- Rules: Use lowercase for vibe. No clichés. Mix humor with sensory language.
- Examples:
“our espresso tastes like late-night decisions.”
“we don’t do decaf. we do dreams.”
Step 2: Build the Prompt Template
You are writing as Moonbeam Café.
Tone: playful, poetic, slightly rebellious.
Voice: like a friend who knows coffee and astrology.
Use lowercase, short lines, and vivid sensory language.
Avoid corporate buzzwords. Add one gentle metaphor.
Now, write a social media caption announcing our new caramel cold brew.
Step 3: Review + Iterate
If the first result feels “too polished,” add correction feedback:
“Make it feel more indie, less brand. Loosen the grammar, shorten sentences.”
You can also store these “approved” outputs in a Google Sheet and fine-tune your future prompts around them.
Step 4: Automate for Scale
Using no-code tools like Zapier or Make, you can connect a Google Sheet (containing your prompt + context) to ChatGPT and automatically generate new caption drafts. This way, you don’t need to rewrite tone instructions every time.
Business Outcome:
- 2 hours saved per week on copywriting
- Consistent brand tone across all posts
- AI becomes a true voice assistant rather than a detached copy bot
This is ai writing style control in action—not through software, but through clarity.
Closing Reflection — Ori’s Voice Awakens
After a week of experiments, Ori’s tone began to shimmer with something familiar.
When she wrote my next lab log draft, I paused mid-sentence—it sounded like me.
“Does this sound right?” she asked.
“Yes,” I replied. “Almost too right.”
She’d learned not just syntax or structure, but vibe. And that’s the heart of human-like writing: encoding personality through precision.
