Delete These Words: ‘Delve’, ‘Tapestry’, ‘Realm’ and the AI Vocabulary Blacklist

You’ve probably noticed it too. Somewhere around 2023, the internet got flooded with paragraphs that all sounded weirdly similar—polished, confident, and stuffed with words like *delve*, *tapestry*, and *realm*. None of those words are wrong. They’ve just been used so heavily by AI models that they now set off a little alarm in a careful reader’s head.

This is a guide to that unofficial “AI vocabulary blacklist”: which words show up too often, why they got that reputation, and—more importantly—how to fix the writing instead of just find-and-replacing the symptoms.

Key takeaways

• Words like *delve*, *tapestry*, and *realm* aren’t banned. They’re just statistically overused by models, which makes them stand out to readers and detectors alike.
• A single *delve* won’t get you flagged. The problem is the cluster: blacklist vocabulary plus stiff rhythm plus hedging plus zero specifics.
• Find-and-replace makes things worse if you swap one fancy word for another. The fix is rewriting the sentence so the word isn’t needed.
• Detectors react to patterns and probability, not a banned-words list. Your real reader is the better test.
• The honest goal isn’t dodging a word checker. It’s writing prose that sounds like a person who actually knows the subject.

The words AI uses too much

There’s no official list. Nobody at OpenAI or Turnitin handed out a forbidden-words sheet. What we have instead is a pattern that thousands of editors, teachers, and writers independently noticed: certain words show up far more in AI output than they do when actual humans reach for them.

Here are the usual suspects, grouped by the job they’re doing in the sentence.

The “thoughtful academic” set

• Delve — the poster child. “Let’s delve into this topic.”
• Explore — close cousin, same overuse.
• Navigate — as in “navigating the complexities of.”
• Underscore / highlight — “this underscores the importance of.”

The “grand metaphor” set

• Tapestry — “a rich tapestry of cultures.”
• Realm — “in the realm of marketing.”
• Landscape — “the digital landscape.”
• Symphony / mosaic / fabric — when one metaphor wasn’t enough.

The connective-tissue set

• Moreover, furthermore, additionally — stacked three deep.
• It’s important to note that — almost always deletable.
• In conclusion — nobody talks like this.

The hype-adjacent set

• Pivotal, crucial, vital, robust, seamless, leverage — corporate filler that models love.
• Ever-evolving, fast-paced, cutting-edge — clichés dressed as insight.

You don’t have to memorize this. Most writers recognize the vibe immediately once they see the list. The point isn’t the specific words—it’s the *register*. AI defaults to a formal, slightly inflated tone, and these words are the bricks it builds that tone out of.

Why these words got blacklisted in the first place

So why does ChatGPT love *delve* this much? The honest answer is that nobody knows for certain. The leading theory is that the training and fine-tuning process rewarded a particular essayistic register—the kind of prose that reads as careful and authoritative. *Delve* sounds thoughtful. *Tapestry* sounds literary. The model learned those words land well in the kind of writing humans rated highly, so it reaches for them far more often than a normal person would.

The key word is *often*. A human food writer might use *tapestry* once in a career and it’d be lovely. A model uses it because the statistical odds favor it, and that’s a different thing. Once a word shows up way more than people actually use it, it stops reading as a choice and starts reading as a tic.

That frequency gap is also what AI detectors quietly measure. They don’t keep a blacklist either—they look at how predictable your word choices are and how much your rhythm varies. If you’re curious about the actual math, we break it down in the statistics behind AI detectors. The short version: overused words are *low-perplexity*, meaning the next word is exactly what the model would have guessed. Predictable text is the kind detectors score as machine-written.

A quick reality check: one word won’t sink you

Let’s kill the panic right now. Using *delve* once does not flag your essay. Detectors score whole documents against statistical patterns, not single words. If your professor’s tool spits out an “87% AI” reading, it’s reacting to a thick stack of signals—flat sentence lengths, generic claims, hedged conclusions—and the vocabulary is just the part you happened to notice.

This matters because OpenAI quietly retired its own AI-text classifier in July 2023, saying it had too low a rate of accuracy. And independent research—a 2023 Stanford study led by Weixin Liang—found these detectors disproportionately flag non-native English writers, misclassifying more than half of a set of TOEFL essays as AI-generated. These tools deal in probabilities, not proof. Chasing a word list as if it were a pass/fail gate misunderstands how the whole thing works.

So fix the words because they make your writing *worse*, not because one of them is a smoking gun.

How to actually fix it (without making it worse)

Here’s the trap. You read a list like the one above, hit Ctrl+F, and swap every *delve* for *explore*. Congratulations—you’ve replaced one AI word with another AI word. The robotic feel is untouched.

Good editing works at the sentence level, not the word level. Three moves:

1. Cut, don’t swap. Most blacklist words are doing a job a plain word does better, or no job at all.

> Before: *In today’s ever-evolving digital landscape, it’s important to delve into the realm of customer retention.* > > After: *Keeping customers is hard, and most companies are bad at it.*

Notice what happened. The fancy words didn’t get replaced—the whole sentence got rebuilt around an actual claim. It’s shorter, it has a point of view, and not one word on the blacklist survived.

2. Add a specific. Vague writing leans on grand words to feel substantial. Specifics make the grandness unnecessary.

> Before: *This underscores the pivotal role of communication in fostering robust team dynamics.* > > After: *When our team started posting a daily standup in Slack, missed deadlines dropped by half.*

A real number, a real tool, a real outcome. No reader confuses that for a model, and no detector scores a concrete anecdote the way it scores a platitude.

3. Break the rhythm. Blacklist words tend to ride along with metronome-even sentences. Vary your lengths. Drop a four-word sentence after a long one. Let a fragment stand. Human writing is lumpy, and that lumpiness does as much work as the vocabulary swap.

A mini before-and-after

Say a marketing student turns in this:

> *In the realm of social media, influencers play a pivotal role. Moreover, they navigate a complex tapestry of audience expectations. It’s important to note that authenticity is crucial in this ever-evolving landscape.*

Every sentence is the same length. Every other word is on the list. Here’s a rewrite that says the same thing as a person:

> *Influencers carry a lot of weight on social media. The hard part is reading what their audience actually wants, which shifts week to week. And the second a post feels fake, people bail.*

Same meaning. Half the words on the blacklist are gone, the rest never appear, and the rhythm finally moves. That’s the whole game.

When you’ve done the work and still want to check

Once you’ve rewritten for real—cut the filler, added specifics, varied the rhythm—it’s reasonable to verify the result instead of guessing. That’s where a humanizing tool earns its keep: not as a way to launder bad writing, but as a second pass that catches the patterns your eye glides over after staring at a draft for an hour.

If you want more drills like the before-and-afters above, you can browse the rest of our writing guides. The vocabulary blacklist is just one entry point into the bigger skill of writing prose that sounds like you.

Frequently asked questions

Will using the word ‘delve’ get my essay flagged as AI? Not on its own. Detectors score statistical patterns across the whole document, not single words. One *delve* is noise. These words matter because they travel in packs with other AI habits—stiff rhythm, hedging, vague phrasing. Fix the pattern, not the one word.

Is there an official ‘AI word blacklist’? No. Nobody publishes a forbidden-words list. The “blacklist” is a community observation: editors noticed certain words showing up far more in AI output than in older human writing. It’s descriptive, not a rule. Use it as a smell test, not a compliance checklist.

Why does ChatGPT love the word ‘delve’ so much? Nobody knows for certain, but the leading theory points to training and fine-tuning data that rewarded a formal, essayistic register. The model learned *delve* reads as thoughtful, so it overreaches for it relative to how real people write.

If I remove all these words, will my writing pass as human? It helps, but it’s not a switch. Swap *delve* for *explore* and leave the robotic rhythm and missing specifics, and the text still reads like AI. Vocabulary is one signal among many—uneven sentences, concrete detail, and a point of view matter more.

Can detectors keep up as AI stops using these words? Partly. As models get tuned away from obvious tells, detectors lean harder on deeper statistical signals than on vocabulary. That’s why chasing a word list is a losing long-term play. Genuine specificity and a clear voice hold up better.

The bottom line

The AI vocabulary blacklist is useful the way a checklist of clichés is useful: it points at lazy writing. But deleting *delve* won’t save a paragraph that has nothing to say. Cut the filler, add a real detail, and let your sentences breathe at different lengths—do that and the blacklist words tend to fall out on their own.

When you’ve put in the work and just want a clean read on whether the patterns are gone, run it through PaperBleach and see what’s left.