What kind of writer are you? Copilot can tell

I recently used Copilot to do something surprisingly useful: help me understand how I write. Not to generate more content.

The problem is not “can AI write text?”

The problem is: can AI help me write text that does not sound like generic AI output?

So, I asked Copilot to analyze the work content it could access — especially outbound emails and Teams messages — and extract a “Chris voice” style guide.

This was the original prompt:

I want to write a "Chris Style guide" that embodies how I write and talk.
1. Analyze all my outbound emails from the past year
2. Analyze as much Teams messages from me as you can. Ensure only messages I wrote are used
3. Write a "Chris voice" style guide, that includes idioms, phrases etc. 

The objective is to help AI and LLMs produce content closer to what I could produce.

> Small technical caveat: “all” here really means “what Copilot can ground on in my Microsoft 365 context.” Permissions, indexing, retention, product boundaries, and available context still matter. This is not a magic unrestricted export of everything I have ever written.

I also asked ChatGPT to perform a similar analysis based on my previous interactions there. Then I merged both outputs. The result was much more useful than I expected!

A few things stood out.First, it captured the enterprise / technical vocabulary surprisingly well.

Not just surface-level terms, but the way I frame problems:

• start from the concrete situation
• make constraints explicit
• avoid hype
• avoid salesy content
• prefer technical accuracy over polished marketing language
• explain trade-offs
• end with something usable

That part matters a lot to me.

I do not want AI to make my content “more inspiring.”

I want it to make the simple path clear, the constraints visible, and the recommendation actionable.

Second, it identified a strong pragmatic bias. Apparently, I do not naturally write in abstract strategy language for very long 😅

I tend to move quickly toward:

• what is happening
• what we are trying to achieve
• what is blocking us
• what trade-offs we have
• what I recommend doing next

That is actually a good reminder for prompt engineering. A good voice prompt should not just say:

“Use a professional tone.”

That is too vague. It should say things like:

“Start from the real-world constraint. Avoid corporate fluff. Be technical when the topic is technical. Prefer structured reasoning. Make the recommendation explicit.”

That is much more operational.

Third, it picked up multilingual differences. In English, my writing tends to be more direct, structured, and straight to the point.

In French, I apparently use more conversational framing, more oral transitions, and more context before the actual recommendation.

Which is fair. And probably very French 🙂

Fourth, it tried to model my humor. But it needs more work.

The important part is not that I now have a perfect “Chris prompt.” I do not. The useful part is that I now have a reusable style guide that turns voice into constraints.

Not:

“Write like me.”

But:

“Here is how I reason, structure, reject fluff, explain trade-offs, switch between English and French, and decide what good output looks like.”

That is a much better interface between me and AI.

My takeaway: personal AI writing does not start with a better model. It starts with a better description of what “good” means for you.