Sentence Structure

The "It's not X -- it's Y" pattern, often with an em dash. The single most commonly identified AI writing tell. Man I f*cking hate it. AI uses this to create false profundity by framing everything as a surprising reframe. One in a piece can be effective; ten in a blog post is a genuine insult to the reader. Before LLMs, people simply did not write like this at scale. Includes the causal variant "not because X, but because Y" where every explanation is framed as a surprise reveal, the em-dash dismissal "X -- not Y", and the cross-sentence reframe where the same noun is negated then repositioned: "The question isn't X. The question is Y."

“It's not bold. It's backwards.”

The dramatic countdown pattern. AI builds tension by negating two or more things before revealing the actual point. Creates a false sense of narrowing down to the truth.

“Not a bug. Not a feature. A fundamental design flaw.”

Self-posed rhetorical questions answered immediately in the next sentence or clause. The model asks a question nobody was asking, then answers it for dramatic effect. Thinks this is the epitome of great writing.

“The result? Devastating.”

Repeating the same sentence opening multiple times in quick succession.

“They assume that users will pay... They assume that developers will build... They assume that ecosystems will emerge... They assume that...”

Overuse of the rule-of-three pattern, often extended to four or five. A single tricolon is elegant; three back-to-back tricolons are a pattern recognition failure.

“Products impress people; platforms empower them. Products solve problems; platforms create worlds. Products scale linearly; platforms scale exponentially.”

Filler transitions that signal nothing. AI uses these phrases to introduce new points without actually connecting them to the previous argument. Also includes: "It bears mentioning", "Importantly", "Interestingly", "Notably".

“It's worth noting that this approach has limitations.”

Tacking a present participle ("-ing") phrase onto the end of a sentence to inject shallow analysis that says nothing. The model attaches significance, legacy, or broader meaning to mundane facts using phrases like "highlighting its importance", "reflecting broader trends", or "contributing to the development of...".

“contributing to the region's rich cultural heritage”

Using "from X to Y" constructions where X and Y aren't on any real scale. In legitimate use, "from X to Y" implies a spectrum with a meaningful middle. AI uses it as a fancy way to list two loosely related things. "From innovation to cultural transformation" -- what's in between???? Nothing!

“From innovation to implementation to cultural transformation.”