Most advice on this topic is vague. "Write naturally." "Add a human touch." "Vary your sentence length." That's not useful because it doesn't tell you what to change.
Here's what actually causes AI content to read as AI-generated, and what you can do about each one.
The vocabulary problem
AI models have preferred words. Not because they're accurate, but because they appear frequently in the training data in contexts that match the prompt.
The worst offenders: delve, tapestry, testament, multifaceted, nuanced, pivotal, embark, it's worth noting, in conclusion, in today's fast-paced world.
These words aren't wrong. They're just statistically overrepresented in AI output, which means readers have learned to associate them with generated content. A human writer would rarely reach for "delve" when "look at" does the same job.
Fix: build a banned word list and put it in your prompt. Explicitly. Not "avoid clichés" but "never use the following words: delve, tapestry, testament..."
The structure problem
AI defaults to the same essay structure every time: hook, three supporting points, conclusion that restates the hook. It's the structure that got good marks in school essays, and the models have absorbed it completely.
Real writing doesn't work this way. It follows the argument, not the format. A good piece about a technical topic might open mid-thought, or with a specific example, or with a question that doesn't get answered until paragraph four.
Fix: tell the model explicitly what structure not to use. "Do not use a three-part structure. Do not write a conclusion that restates the introduction."
The hedging problem
AI qualifies everything. "It's important to note that..." "While there are many factors to consider..." "Some people may find that..."
This hedging comes from the model trying to be accurate and fair. It's learned that absolute statements sometimes get pushed back on, so it softens everything by default.
Human writers take positions. They say "this doesn't work" not "this may not work for some use cases."
Fix: instruct the model to take positions, use specific numbers and examples instead of generalisations, and remove qualifiers. "Do not use phrases like 'it's worth noting' or 'some may argue'. Make direct statements."
The opener problem
AI almost always opens with a statement about the topic's importance or relevance. "Content marketing has never been more important." "In today's competitive landscape..." "More businesses than ever are discovering..."
These openers are weak because they tell the reader nothing they didn't already know, and they delay getting to the actual point.
Fix: ban scene-setting openers. "Do not open with a statement about why the topic matters. Do not open with a statistic about industry trends. Start with a specific observation, example, or claim."
Why this matters
These aren't small stylistic preferences. They're the difference between content that gets read and content that gets ignored. Readers can detect AI writing faster than they can articulate why, and they've learned to trust it less.
The technical fixes above work. But they require specificity in your prompts, and they need to be maintained as models update and develop new patterns.
That's most of what WriteHQ is built around. The prompts are a maintained list of structural and vocabulary constraints, updated as new patterns emerge. If you're generating content at scale, that maintenance work matters.
WriteHQ generates blog posts, product descriptions, and marketing copy that reads like it was written by a person. From £9.99/month at writehq.app.
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