A founder I respect sent me a DM in March. We'd been chatting on and off for a year. Her question was three words.

"Did you outsource?"

I had not outsourced. I was confused. She elaborated — she'd seen me reply on a Reddit thread the day before, and the reply sounded nothing like the person she'd been DMing for the past year. "It read like an SDR." She had assumed I'd hired one and forgotten to mention it.

I went and re-read the reply. She was right. It was the third reply I'd drafted with ChatGPT that day, and by then I'd given up rewriting the AI-voice out. The reply said "I'd love to dig into your use case" which is, I want to be clear, a sentence I have never said aloud in my life. I closed the laptop.

This post is about the smell. Why ChatGPT writing has it. Why it gets worse the more you use ChatGPT for replies. And what an actual fix looks like, because "rewrite every line until it sounds like you" is not a fix, it's a job.

The smell is real, and the smell is universal

If you've read more than five AI-generated replies on Reddit or LinkedIn, you've already learned the tells without thinking about it.

The em dashes in the wrong places — not where you'd naturally pause, but where the model wants to look thoughtful. The three-sentence paragraphs that all open with the same rhythm. The slightly-too-eager opener: "I love how you framed this," "I really appreciate the question," "Great point about X." The word "delve". The word "leverage". The phrase "in today's fast-paced landscape." The sentence that ends with "and that's what makes all the difference" or some variant of it. The closer that promises to "dive deeper" or "explore further" or "circle back."

None of these is wrong on its own. Most of them are real things a real person might write once. The smell isn't the individual phrase. The smell is the combination, at a frequency higher than humans produce naturally, in service of a tone that's slightly too eager to be liked.

The reason this is universal is that ChatGPT — and Claude and Gemini, mostly the same problem — were tuned on a particular kind of writing. Helpful, slightly formal, optimistic, professional. That tone is fine in a customer-support email. It is conspicuous on Reddit, where the dominant register is dry, skeptical, and self-deprecating. A reply that sounds like an SDR in a community of people who hate SDRs gets ignored at best, banned at worst.

You can rewrite it line by line. That takes the four minutes I described in Post 1 and turns it into four minutes per reply, forever. You don't have four minutes per reply forever. You'll quit by week three.

Why ChatGPT can't shake it

The model is trying to sound like a competent generalist. That's the floor it was tuned to. With no information about what you sound like, that's the floor it produces. Adding "be more casual" or "match my tone" to your system prompt makes it sound like a competent generalist pretending to be casual, which is its own distinct register and is somehow worse.

The fix isn't a better prompt. It's giving the model a sample of you and asking it to write as the same person who wrote that sample.

The way this works in practice is the same shape as the product-grounding I wrote about in Post 3. You provide examples — replies you've sent, tweets you've written, paragraphs from your blog. The system embeds them. Every time you draft a reply, it retrieves the chunks of your writing most relevant to the kind of reply you're writing (Reddit-thread-about-pricing pulls your past pricing replies; X-thread-about-launch pulls your X threads). Those chunks go into the model's context alongside the thread. The draft comes out shaped like you.

The retrieval is what makes it work. A "voice prompt" that's the same paragraph every time is what ChatGPT already does badly. A retrieval over actual writing means the model sees your real tone for the kind of reply it's drafting, which is a much harder fact to ignore than a one-line instruction.

The five to ten examples that matter

You don't need fifty. You need five to ten that capture you when you're not trying.

In our voice profile flow, we ask for examples that fit three buckets:

A reply to a stranger. Reddit or LinkedIn comment, ideally where you were being helpful, not pitching. This is your default "I'm a normal person on the internet" voice.
A reply to a friend or peer. Something more casual, where you'd use a contraction without thinking. This is your at-the-bar voice.
A bit of long-form. A short blog paragraph, a Notion doc, a tweet thread. This is your thinking voice.

What we don't want is the polished marketing copy from your website. The website voice is your brand voice, which is fine on the website, but it's not what we want in a Reddit reply. The Reddit reply has to sound like you sent it from your phone after dinner.

Once those examples are in, the engine keeps refining. Every time you edit a draft, the edits get logged. After a few weeks the system has a rolling picture of "the things Andy almost always changes." Generic openers get cut before they're suggested. The phrase "happy to share" never comes back. Em dashes show up at the rate I actually use them, which is real but not three-per-paragraph.

The compound effect, eight weeks in

This is the part I wasn't expecting.

The first effect is obvious — you stop hating every draft. The hidden tax of "five minutes of rewriting to de-AI this" disappears, which is what makes the reps sustainable.

The second effect surprised me. People started DMing me again. The friend who'd asked if I'd outsourced sent another DM in April: "much better, you're back." A handful of strangers from r/SaaS started a thread on a different topic two weeks after I'd replied to them. The voice was consistent enough across my Reddit replies that they recognized me as the same person, and the next reply could be a slightly more personal version of the previous one. Continuity. That's what the AI smell was killing.

The third effect: more inbound. Not by a lot, but noticeably. The replies didn't read like a marketer fishing for clicks, so people were willing to engage with the comment first. The clicks came later.

What this is not

This is not a guarantee you'll fool anyone. Anyone reading carefully can still spot AI-flavored writing in places. The voice profile gets you from "obviously AI" to "sounds like a person who might have used AI to draft this, which is fine." That's the goal. Not deception — just removing the conspicuous markers that make a thoughtful comment look like marketing.

It's not a substitute for editing. You still read every draft. The voice profile means you're editing one or two lines per reply, not eight.

It's not a substitute for being someone with a voice worth modeling. If your existing replies sound like marketing copy, the voice profile will produce more marketing copy. The way out of that is to write three replies a week, by hand, where you're not pitching anything. Then feed those in. The profile is a mirror.

If your friends have stopped engaging with your replies

That's the actual leading indicator. Not signup count. Not click-through. The friend who used to like your comments doesn't anymore. The peer who used to reply to your Reddit posts has gone quiet. That's the smell working in the wrong direction.

Thread Otter has a 14-day trial, no card. Paste five to ten examples of your writing. Generate three drafts in a row. See whether the third one sounds like you. The first 100 Solo signups lock in $19/mo for life — the Founding 100 cohort, counter live on the pricing page.

threadotter.com/pricing

The DM I got in March wasn't a complaint. It was a signal. The replies my friends could no longer recognize were the ones converting nobody, because of course they weren't. Sounding like a person is the price of entry, not a bonus feature.