Claude is fast and tidy, but it leaves patterns behind. A neat little contrast here, three matching clauses there, two sentences that open the same way, a vivid word chosen because it pops instead of because it belongs - readers notice these habits long before they can explain them. And once they sense the machinery under the prose, your authority starts to slip.

This book shows you how to spot those patterns and clear them out the way a good editor would, except the editor is a system you build for yourself.

You write with Claude, you publish under your own name, and you want the work to sound like you. That's who this is for: nonfiction authors, newsletter writers, technical communicators - anyone using AI to draft and who has felt a paragraph go dull without knowing why. You don't need a linguistics background. Each device is named, shown in context, and paired with the fix that removes it, so by the end you can look at a flagged line, understand what triggered it, and revise without flattening your voice.

Across the chapters, you assemble detectors for the major tells - echoes, parallel structures, banned constructions, choppy runs, negation frames, repetitive openings, thin vocabulary - and then add two layers that commercial classifiers actually weigh: the document-level patterns (flat pacing, overlong elaboration chains, neutralized stance) and the statistical layer (punctuation patterns, nominalization load, meta-commentary density, excess-vocabulary spikes). Three passes in all, each catching a different level of the text, all running before a chapter is considered finished.

What you leave with is a method you can apply to any model's output, a pipeline that keeps your prose honest, and the language to describe exactly why a draft feels artificial. The book itself went through the same system it teaches you to build.