Six months ago, you could spot AI-generated text by its polished grammar, rigid essay structure, suspicious fondness for em dashes – and, of course, the inevitable emoji bullets (🔥🚀✨). The real giveaway, at least to my eye and ear, isn’t the emojis or the punctuation. It’s the cadence.
AI writing has a rhythm problem. The sentences are clipped. Overly dramatic. Split into one-line paragraphs that feel more like infomercials than journalism.
“The truth? This wasn’t SEO causation. It was a stock market correction.”
“They were left behind. They were angry. They weren’t your people.”
On the page, this is nails-on-chalkboard grating. It doesn’t read as conversational. It reads as performative. In my opinion, this is, without a doubt, AI’s most recognizable stylistic fingerprint.
A Brief History Of The AI Cadence
This rhythm predates AI. It has been the language of speechwriters, preachers, and copywriters long before GPT entered the chat. Think Reagan’s addresses, Clinton’s campaign rallies, Obama’s campaign speeches, Churchill’s wartime broadcasts, and Blair’s conference speeches. Each leaned on rhythm and repetition to generate a great deal of emotion out of a speck of substance. Pair that with Captain Kirk’s famously staccato delivery, televangelists’ sermons, or TED Talks built around dramatic pauses, and you see how cadence can make small or mundane ideas feel powerful and deep.
That style used to stay in its lane. Where print valued density and clarity, speech valued brevity and rhythm. Readers could re-read; listeners could not. Editors enforced writing standards and styles and the economics of print rewarded information density over theatrics. As a result, this cadence lived solely in spoken word. It lived in speeches and sales copy, and not in essays and articles.
AI collapsed those boundaries. Because LLMs cannot (or chose to not) differentiate between a stump speech, a YouTube transcript, and a white paper, they overindex patterns designed to persuade aloud and repurpose them for the written page. Now, we are inundated with technical articles that read like motivational talks.
Why AIs Default To This Cadence
The AI cadence is not an accident – it’s a reflection of what models were most heavily trained on. Large language models have been fed a disproportionate amount of spoken-word material: transcripts of speeches, news reports, debates, interviews, webinars, podcasts, and video scripts. These aren’t “written texts” in the traditional sense; they are spoken performances converted into text.
Why so much spoken-word data? Because it’s cheap and plentiful. Back when I was running my ISP, I loved radio and TV for advertising and news mentions because it was far less expensive than buying or winning space in print. Broadcasters had 24 hours a day to fill, and local stations were always desperate for content. Print, on the other hand, is expensive. Every page of a newspaper, magazine, or book…
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