From Vague to Vivid: A Word-by-Word Rewrite of an Abstract Sentence

Here’s a sentence that looks fine until you actually try to picture it: “Our solution leverages various tools to drive meaningful improvements across the organization.” Read it twice. Did anything appear in your head? Probably not — and that’s the problem. Abstract writing slides past the eye without leaving a single image behind.

This post takes that exact sentence and rebuilds it one word at a time, so you can watch vague turn into vivid in slow motion.

Key takeaways

• Abstract sentences fail because the reader can’t picture anything — concrete nouns, real numbers, and specific actions fix that.
• You don’t rewrite the whole sentence at once. You interrogate it word by word and ask each vague word to earn its place.
• Concrete writing tends to read more human to AI detectors, because specificity raises unpredictability — the opposite of generic filler.
• The goal isn’t fancier words. It’s words a reader can see, count, or touch.

Why abstract sentences feel empty

A reader’s brain runs on pictures. When you write “improvements,” nothing renders. When you write “the checkout page loaded in under two seconds instead of nine,” something does. The first version asks the reader to trust you. The second lets them see it for themselves.

Abstraction isn’t always bad. You need it to summarize, to conclude, to zoom out. The trouble starts when every word is abstract and nothing underneath holds it up. That’s when prose turns to fog — technically grammatical, emotionally weightless, and weirdly hard to remember five minutes later.

There’s a second reason to care. Generic abstraction is the house style of large language models. They were trained on oceans of corporate-flavored text, so “leverage,” “various,” “meaningful,” and “across the organization” are their comfort food. If your writing leans on the same words, it reads like everything else — to humans *and* to machines. Specific detail does the opposite. It pushes up the unpredictability of your text, which is part of what detectors actually measure. (Worth saying plainly: detectors report a probability, not proof, and none of this is a magic pass. Specific writing is just less templated.) If you’re curious how that scoring works, we broke it down in the statistics behind AI detectors.

The interrogation method

Making abstract writing concrete isn’t about swapping in bigger words. It’s a small, almost annoying habit: stop on each word and ask, “Can the reader see this, count this, or touch this?” If not, the word is on probation. Either it earns its place with a concrete anchor nearby, or it goes.

Let’s run our sample sentence through it.

> Our solution leverages various tools to drive meaningful improvements across the organization.

“Solution”

What is the solution? A “solution” is a placeholder for a real thing you haven’t named yet. Say it was a shared dashboard the support team built. So “solution” becomes “the support dashboard we built.” Now the reader knows the actual object.

“Leverages”

Nobody leverages anything in real life. They use it, run it, plug it in, lean on it. “Leverages” is a word that exists mostly to sound serious. Replace it with the plain verb for what literally happened: the team “pulls data from.”

“Various tools”

“Various” is the single most evasive word in business writing. It means “I don’t want to list them,” which usually means the writer either doesn’t know or didn’t bother. Name them. Here: “Zendesk, our billing database, and a Slack channel.” Three concrete nouns beat one vague one every time.

“Drive meaningful improvements”

This is the part that sounds like it’s saying something. It isn’t. *Improved what? By how much? Meaningful to whom?* Pin it down with a number and an outcome: “cut average response time from nine hours to two.”

Notice that a real number does double duty. It’s concrete, and it’s specific enough that no one could have guessed it — which is exactly the kind of detail that reads as human.

“Across the organization”

Across *which* organization, and who actually felt it? Probably not the whole company. Probably one team. Name them: “for our forty-person support team.”

Putting it back together

> Our support dashboard pulls data from Zendesk, our billing database, and a Slack channel, cutting our forty-person support team’s average response time from nine hours to two.

Same idea. Completely different sentence. You can see the dashboard, count the hours, picture the team. It’s a hair longer than the original, but every added word bought you an image. The original bought you nothing.

(To be clear, those numbers are invented for the example — the point is the shape of the fix, not the figures.)

A second pass, because once is rarely enough

Concrete writing isn’t a one-and-done filter. The first pass catches the obvious fog. A second pass catches the words you were too close to notice.

Take a paragraph from a student essay:

> Social media has had a significant impact on how people communicate, affecting various aspects of their daily interactions in numerous ways.

Run the interrogation:

• “significant impact” — impact you can’t measure isn’t impact, it’s a claim. What changed?
• “various aspects” — there’s “various” again. Which aspects?
• “numerous ways” — this is “various” wearing a different hat. Cut it.

A grounded rewrite:

> Texting replaced the phone call for my generation. My roommate and I have lived together for two years and have never once spoken on the phone — we send forty texts a day instead.

That’s a real claim with a real number and a real scene. It argues the same point as the original, but now there’s a person in a room with a phone in their hand. The reader believes it because they can see it.

If you want to drill specific techniques like this, there are more articles on writing craft worth a look.

When to keep the abstraction

This isn’t a war on abstract words. Some sentences are *supposed* to zoom out. “Trust is fragile” is abstract on purpose — it’s a thesis. The mistake is leaving it naked. Pair the abstraction with a concrete instance and it lands:

> Trust is fragile. One support ticket ignored for nine hours, and a customer who’d been with us four years closed her account in a single afternoon.

The abstract sentence states the lesson. The concrete one earns it. You need both — the claim and the photograph. Writing that’s all abstraction floats away; writing that’s all concrete detail never adds up to a point. Vivid prose alternates.

A quick rule of thumb: every abstract claim should have a concrete neighbor within a sentence or two. If three abstract sentences pile up with nothing you can picture, the reader has quietly stopped paying attention.

A short checklist you can actually use

When you reread a draft, circle every word that fails the see-count-touch test. Common offenders:

• Hollow nouns: solution, aspects, factors, resources, things, impact, value.
• Inflated verbs: leverage, utilize, facilitate, optimize, drive, enable.
• Quantity dodges: various, numerous, several, many, a range of, a number of.
• Importance filler: significant, meaningful, robust, key, crucial.

You don’t have to delete all of them. You have to make each one prove it has a concrete anchor nearby. The hollow noun “resources” survives if the next clause says “two part-time editors and a $400 software budget.” Without that anchor, it’s fog.

Frequently asked questions

Is making writing concrete the same as making it shorter?

Not always. A concrete sentence is sometimes longer than the vague version because you’re adding real detail — a number, a name, a specific action. The win isn’t fewer words, it’s fewer empty ones. You cut filler like “various” and “aspects,” then spend that space on something the reader can actually picture.

Won’t adding specific details make my writing too long?

Specificity replaces vagueness rather than piling on top of it. One concrete example often does the work of three abstract sentences, so the total usually shrinks. If you find yourself adding detail without removing any abstraction, that’s when length creeps up — trade, don’t stack.

Does concrete writing actually help with AI detection?

It tends to. Generic, abstract phrasing is what language models default to, so detectors see it constantly. Concrete details — odd numbers, specific names, lived particulars — raise the unpredictability of your text, which is part of what detectors measure. It’s not a trick, and it’s not a guarantee. Specific writing is just genuinely less templated, and detectors report a probability, not a verdict.

How do I know if a word is too abstract?

Ask whether you could photograph it or count it. “Improvement” can’t be photographed; “forty fewer support tickets” can be counted. “Resources” is a fog; “two part-time editors and a $400 software budget” is a picture. If a word survives only because it sounds professional, it’s probably abstract filler.

What if my topic really is abstract, like justice or freedom?

Abstract topics still need concrete anchors. You don’t make “freedom” concrete by defining it harder — you ground it in a scene: someone crossing a border, a curfew lifting, a vote counted. Big ideas land through small, specific instances. The abstraction is the conclusion; the concrete detail is the evidence that earns it.

Closing

Vague writing is the easiest writing to produce and the easiest to ignore. The fix is slow and a little tedious: stop on each word, ask if the reader can see it, and replace the ones that can’t. Do that for a few drafts and it becomes automatic.

If you’ve got a piece that reads flat and you can’t tell why, paste it in and run it through PaperBleach — the heatmap will show you exactly which sentences are coasting on abstraction so you know where to start cutting.