Aresume is no longer a document. It is a signal, parsed in milliseconds by systems trained on a thousand other applicants. This issue: how to write for the reader you cannot see — and be recognised by the reader you can.
Contents
Every article on this page is a feature of the product. Read in order, or step in where your curiosity takes you.
Real-time alignment and a detailed anatomy of every percentage point.
The missing vocabulary, recovered — for ATS readability and relevance.
An archive for drafts, revisions, and application histories.
Composed to the letter of the job, in the tone of the trade.
Trends across a season of applications, plainly reported.
Side-by-side comparisons of what worked, and when.
Feature · 01
In which the machine shows its work — the phrases it found, the ones it couldn’t, and where, precisely, the signal weakens.
The machine that reads your resume first is not the hiring manager. It is a parser — indifferent to narrative, allergic to metaphor. Our analysis returns to you what it sees, phrase by phrase, skill by skill, so the next line you write is aimed at a target you can finally, clearly, see.
“The finest resume is not the one that says the most, but the one that is read most carefully.”
— from the masthead
Feature · 02
Hiring rarely fails on merit; more often, on vocabulary. We read the description, recover the phrases it was built on, and hand them back to you in order of their weight — with quiet suggestions for where, in your own voice, they might be answered.
The Method
A single file — PDF or DOCX — is all we ask. The rest we read on our own time.
The system returns your resume to you, annotated. Nothing is hidden from view.
With a revised draft and a letter to match, you write the next chapter yourself.
— The Invitation —
Your next draft deserves a patient reader. We are waiting in the margins.