Humanize AI text
AI wrote it like everyone. A writer makes it sound like you.
Humanizing is not sprinkling in typos to fool a detector. It is shaping language around real context, intent, experience and tone so the words are honestly yours. Post the text and a sample of your voice; a vetted writer does the rest.
The gap
Where the generated version stops.
Model output has a recognisable centre: balanced, hedged, agreeable, generic. Your readers know you. They notice when you sound like everyone. The fix is judgement and specificity, not tricks.
What the writer does
The work that usually follows.
Not every job needs all of it. Most need more than the requester expected. Each line becomes part of the definition of done or a priced addition.
- Decide who is speaking and to whom; write that down
- Adjust tone: formality, warmth, confidence, humour, to match the speaker
- Replace generic claims with specific experience, numbers and names
- Cut the filler patterns: triads, "in today's world", empty summaries
- Add context the model could not know: history, constraints, the real reason
- Check nuance and responsibility: what are you actually promising?
- Read aloud; fix rhythm and flow
- Final editorial review by the person whose name is on it
Starter definition of done
What "finished" means for this kind of work.
Edit this when you post, or let the writer propose a tighter one at Match. It is what they quote against, work toward and submit against, and what you approve against.
Who posts this
Founders and executives, communicators, job seekers with a generated letter, anyone publishing under their own name.
Who finishes it
Writers with a voice-matching specialty, vetted for exactly this.
Reviewed by a peer in the same craft, proven on a paid trial, with a public record of jobs finished and first-round approval rate.
Post it. A writer finishes it.
Funded before work starts. Paid when you approve. Every change on the record.