How do I check if AI social posts still sound like me?
Mix real posts with AI drafts, ask someone who knows your writing to pick yours; if they spot AI instantly, add source posts or edit before you scale. You are the worst judge of your own AI drafts after the third edit—familiarity hides the tells. A short blind test restores honesty.
Why you stop noticing the tells
After enough generations, generic cadence starts to feel “fine.” That is the failure mode behind voice-cloned vs generic AI posts.
Common drift:
- Hooks that sound like every other LinkedIn carousel
- Smooth paragraphs with no personal specificity
- Soft claims you’d never make without a source
- Identical rhythm across X, LinkedIn, Facebook Pages, and Instagram because you didn’t rewrite
Fatigue is not a strategy. Brand rules catch banned phrases; they don’t catch “this sounds like a capable stranger.” Voice checks need a human who still has distance.
Phone drafts make it easy to approve on the go; that’s when drift accelerates. Build a deliberate test before volume.
The blind-test method
Keep it small and repeatable.
- Pull 3–5 real posts you actually published and still like
- Generate 3–5 AI drafts for similar intents (same profile, current archive)
- Strip dates, platform chrome, and obvious giveaways
- Shuffle into one list
- Ask someone who knows your writing: “Which ones are mine?”
- Optional second pass: “Which ones would you believe I posted tomorrow?”
Who to ask:
- A colleague or editor who reads you weekly
- A peer founder who can spot your metaphors
- For agencies: the client contact who owns the voice—not only the account manager who drafts
Don’t tip them with “the AI ones are smoother.” Don’t use only your best viral hits as the real set—include normal posts.
What “caught as AI” means
If they pick your real posts cleanly and flag drafts as off, treat that as a process signal, not a personality flaw.
| Result | Interpretation | Next move |
|---|---|---|
| They confuse real and AI often | Voice loop is healthy enough to schedule carefully | Keep rules + light edits; retest after archive changes |
| They spot AI instantly | Archive, rules, or editing bar is weak | Add history / tighten templates / add personal detail before scale |
| They like AI more than real | Tone may be drifting toward generic “polished” | Prefer your real quirks; reject smoothness that isn’t you |
“Caught as AI” is useful when it prevents a week of scheduled posts that train the audience (and your future archive) on the wrong voice.
Fix with history, templates, and personal detail
When the blind test fails, fix inputs—not just the single draft.
History
- Import more posts that sound like you, not only outliers
- Drop thin reshare captions that dilute the sample
- Separate client/brand profiles so voices don’t blend
- Keep your usual openers and sign-offs when they’re real habits
- Enforce platform-native length—don’t ship the same blob everywhere
- Use brand rules for claims and banned phrases so drafts don’t invent polish
Personal detail
- Add one concrete artifact only you would mention (tool, moment, constraint)
- Prefer specific examples over abstract advice
- Edit out fake images and invented stats every time
Then regenerate or heavily edit—and run the blind test again on a fresh mix.
Test before you scale
Scale means more scheduled posts, more platforms, or Agent Mode. None of those fix a failed smell test; they multiply it.
Before you scale:
- Pass at least one blind test with someone who knows the voice
- Confirm brand rules are written and applied
- Rewrite per platform instead of cloning captions
- Keep Agent Mode off until the loop is boringly consistent
Agencies: run the test per client voice. A passing test for Client A says nothing about Client B.
Retest when you change the archive a lot, onboard a new writer, or notice engagement that feels “polite but not you.”
Make the test a habit, not a one-off
Run a lightweight blind test:
- After the first import (baseline)
- After you add a large new batch of source posts
- Before turning on higher volume or Agent Mode
- When a new teammate starts drafting for the brand
Keep a simple log: date, who reviewed, pass/fail, what you changed (more history / stricter edits / tighter rules). You’re not chasing a vanity score—you’re preventing a week of scheduled posts that teach the audience the wrong voice.
Platform note: a draft can pass on LinkedIn length and still fail on X if you didn’t rewrite. Blind-test the platform-native version you plan to ship, not only the long master copy.
Try Free
Mix real and AI, get a blind read from someone who knows your writing, and fix history/templates/detail before you scale. Soft proof is also the heart of what PostMimic is. Start Free at https://postmimic.app to draft from real posts and keep rules on the profile—then upgrade when allowance or multi-profile needs outgrow Free’s 5 cloud AI posts one-time.