Editorial handbook

Common AI Readability Mistakes (and How to Fix Them)

Written by

Jakob Kamender · Founder of Textorum

Published

July 15, 2026

1. Long, overloaded sentences

AI Readability dimension · Sentence Clarity

A long sentence is not automatically a bad sentence, but sentences that carry three or four ideas at once are the single most common readability problem we encounter. They usually happen when a writer tries to qualify a claim, add a nuance, and pre-empt an objection without breaking the flow. The result is a sentence the reader has to re-read to parse — and that a model has to guess at when extracting a quotable line.

For a human reader, an overloaded sentence taxes short-term memory: by the end of the sentence, the reader has forgotten how it began. For an AI system, the effect is more concrete. A summarizer has to decide which clause is the main claim; a quoting system has to decide where the quote begins and ends. Long, sub-clause-heavy sentences make those decisions unreliable.

Checklist

• One idea per sentence.
• If a sentence has more than two commas, consider splitting it.
• Move qualifiers into a separate sentence when they carry their own idea.
• Read the sentence aloud; if you run out of breath, it is too long.

Takeaway · Split any sentence that a reader would have to re-read to understand.

2. Weak or missing headings

AI Readability dimension · Structural Organization

Headings are the map of a page. Weak headings — decorative labels, clever puns, single-word tags — force the reader to enter every section to find out what it is about. Missing headings force the reader to treat the whole page as one long block. Both problems reduce navigation and both weaken how AI systems segment a page into topical units.

A useful heading answers a question the reader might ask, or describes the promise of the section in plain terms. "The problem" is a weak heading; "Why long sentences hurt clarity" is a useful one. Descriptive headings also give a language model a small, reliable signal about what the following passage is likely to contain.

Checklist

• Every H2 describes what the section answers, not how it feels.
• Heading levels reflect the argument, not the visual design.
• Skim only the headings — the page should still make sense.
• Avoid stacking two headings with no content between them.

Takeaway · A reader who scans only your headings should already understand your page.

For a deeper look at how structural signals feed into the AI Readability Score, see The AI Readability Score Explained.

3. Inconsistent entity names

AI Readability dimension · Entity Consistency

Writers naturally vary their language to avoid repetition. In many contexts this is a virtue. When the varied words are the names of people, products, companies, or core concepts, it becomes a problem. A single entity called by four different names across a page is harder to track for a reader, and harder to attribute for a model that is trying to decide who did what.

The rule is not to repeat the same word every time. It is to use one canonical name for each entity, plus a small number of clearly resolved shorthands. A pronoun with an ambiguous antecedent is not a shorthand; it is a hidden inconsistency.

Checklist

• Choose one canonical name for each entity before you start.
• Introduce shorthands explicitly the first time you use them.
• Never let a pronoun span more than one sentence unless the antecedent is obvious.
• Search for every synonym on the page and consolidate where possible.

Takeaway · Call the same thing by the same name every time it matters.

4. Dense paragraphs

AI Readability dimension · Structural Organization

A dense paragraph is one that carries multiple unrelated ideas without a visual break. It is not defined by word count. A 200-word paragraph that develops one idea is fine; a 90-word paragraph that pivots from a definition, to an example, to a caveat, to a call-to-action is not. Density is about the number of ideas per unit, not the number of words per unit.

Dense paragraphs hide their own structure. A reader scanning the page cannot see where one idea ends and another begins. A model extracting a quotable passage has no clean unit to lift. Breaking a dense paragraph into two or three focused paragraphs — one idea each — usually improves both readability and machine interpretability without changing a single word of content.

Checklist

• One idea per paragraph.
• If you can insert a heading in the middle of a paragraph, split it.
• Avoid paragraphs that end with a sentence unrelated to their opening claim.
• Use paragraph breaks to signal a shift in topic, not for visual rhythm alone.

Takeaway · A paragraph is a unit of thought, not a unit of typography.

5. Excessive passive voice

AI Readability dimension · Sentence Clarity

Passive voice has legitimate uses. When the actor is unknown, irrelevant, or intentionally hidden — as in scientific or legal writing — the passive is the right choice. The problem is passive voice used by default: sentences that hide who does what without any editorial reason for the concealment.

Habitual passive voice creates two kinds of friction. For a reader, it delays the subject and forces reconstruction. For a summarizer, it complicates attribution: "the report was compiled" leaves open who compiled it, and the answer often lives in a different sentence, or nowhere on the page.

Checklist

• Search for “was,” “were,” “been,” and “being.” Not all are passive, but most weak passives sit near these words.
• Ask: who does the verb? If the answer is missing, rewrite.
• Keep passive voice when the actor is truly irrelevant or unknown.
• Prefer active constructions in openings, definitions, and instructions.

Takeaway · Passive voice is a tool, not a default. Use it when the actor should recede, not when the writer should.

6. Hedging and filler language

AI Readability dimension · Sentence Clarity

Hedging language — phrases like generally speaking, it could be argued, arguably, somewhat, rather — protects a claim from criticism. Filler language — in order to, at the end of the day, the fact that — pads a sentence without adding meaning. Both appear most often in first drafts, and both survive editing more than they deserve.

Hedges and fillers weaken clarity because they blur what the sentence is actually asserting. They also weaken machine interpretability, because they leave a summarizer with no strong claim to lift. A sentence that says "clarity is important" is quotable; a sentence that says "it could arguably be said that clarity is, generally speaking, quite important" is not.

Checklist

• Delete every hedge you cannot justify.
• Replace “in order to” with “to.”
• Replace “the fact that” with a direct clause.
• Keep the hedges that reflect genuine uncertainty — remove the ones that reflect caution alone.

Takeaway · Only hedge when the underlying claim is genuinely uncertain.

7. Missing answer-first writing

AI Readability dimension · Answer Readiness

Many articles bury their answer. They open with context, then define terms, then compare approaches, and only in the third or fourth paragraph state the point. This pattern is common in academic writing and in draft blog posts. It is not wrong, but it is expensive: a scanning reader may leave before reaching the answer, and an AI summarizer often quotes the opening as though it were the point.

Answer-first writing places the direct answer in the first one or two sentences of the article and of each major section. The supporting argument comes after. This is the pattern used in reference works, FAQs, and definition entries, and it is the shape most consistently associated with passages that AI systems quote as answers.

Checklist

• Open every article with a one- or two-sentence direct answer.
• Open every major section with the same pattern.
• Move context, history, and caveats after the answer, not before.
• If the opening could stand alone as a definition, it is doing its job.

Takeaway · Answer first, then explain — never the reverse.

8. Poor list structure

AI Readability dimension · Structural Organization

Lists are one of the most powerful editorial tools available. They also fail more often than most writers realize. The most common failures are lists whose items are not parallel in structure, lists that mix concepts and examples, lists that number items without ordering them, and lists so long they lose their scanning advantage.

A good list has parallel items — every item is the same kind of thing, in the same grammatical shape. A good list is short enough to scan, usually five to seven items. And a good list uses order when order matters (a process) and bullets when it does not (options).

Checklist

• Every item follows the same grammatical shape.
• Every item is the same kind of thing.
• Numbered lists imply order; unordered lists do not.
• If the list has more than seven items, consider grouping.

Takeaway · A list is a promise of parallelism. Break the parallel and you break the list.

9. Missing examples

AI Readability dimension · Answer Readiness

Abstract writing without examples is the most common cause of "I read it but I do not know what to do." A rule stated in the abstract is easy to nod at and hard to apply. A rule paired with a concrete example — even a short one — is easier to remember, to transfer, and to quote.

Examples also improve answer readiness for AI systems. When a summarizer decides which passage to quote, an abstract rule and a concrete illustration of the rule are often extracted together, and the pair is quoted more cleanly than the rule alone. This is why definition-plus-example is such a durable editorial pattern.

Checklist

• Every abstract rule earns an example.
• Examples are concrete, not gestural (“something like this,” “imagine a case”).
• One vivid example is worth two vague ones.
• Reuse examples across sections when the same illustration applies.

Takeaway · A rule without an example is a suggestion; a rule with an example is a lesson.

10. Weak information hierarchy

AI Readability dimension · Structural Organization

Information hierarchy is the order in which ideas are presented, from most important to least important. It is the invisible skeleton of a page. A page with strong hierarchy answers the reader's most urgent question first and only then works down toward context, caveats, and related material. A page with weak hierarchy treats every idea as equally important, which usually means none of them land.

Weak hierarchy shows up in many forms: a definition buried below three paragraphs of history; a pricing detail hidden inside a feature list; a critical caveat placed above the answer instead of below it. All of these patterns force the reader to search the page for what they came for. They also make the page harder to summarize, because a summarizer that samples the top of the page will surface the wrong point.

Checklist

• The most important idea appears first.
• Each section opens with the answer, then supports it.
• Caveats and history sit after the answer, not before.
• The page reads like a pyramid: point, support, detail.

Takeaway · Order carries meaning. If the reader has to reorder your page to understand it, the page is doing the wrong work.

Editorial checklist

The following checklist consolidates the individual checklists above. It is designed to be run in a final editorial pass, not as a rewriting rule. A page that fails one or two items is not broken; a page that fails most of them is unlikely to serve either a reader or an AI system well.

Mini glossary

A small glossary of the concepts this article uses. Each entry is intentionally short, and each links to further reading where a full article already exists.

Content clarity

The property of a text that lets a reader understand a claim on a single reading. Clarity is not a single feature; it is the result of short sentences, descriptive headings, and consistent terminology working together.

Structured writing

An approach to writing that treats structure — headings, lists, paragraph units — as a first-class editorial concern rather than as decoration. Structured writing is easier to scan for humans and easier to segment for AI systems. See AI Readability Guide.

Entity consistency

The practice of naming each person, product, or concept the same way throughout a document. Consistency reduces friction for readers and reduces attribution errors in downstream tools. Entity consistency is one of the four dimensions of the AI Readability Score.

Answer-first writing

A writing pattern that places the direct answer in the first one or two sentences of an article or section, with supporting argument after. Answer-first passages tend to be quoted more cleanly by AI systems, though no writing pattern guarantees a citation.

Information hierarchy

The ordered arrangement of ideas on a page from most to least important. A strong hierarchy answers the reader's most urgent question first and moves toward context and detail later.

Readability formula

A statistical formula that estimates reading difficulty from features of a text, typically sentence and word length. For a side-by-side treatment of formula-based readability and the AI Readability Score, see AI Readability vs. Flesch Reading Ease.

Frequently asked questions

Conclusion

The problems in this handbook are almost never introduced on purpose. They accumulate through the ordinary work of drafting, revising, and reviewing. A first draft is where hedges settle in. A second draft is where a paragraph picks up an extra idea. A third pass is where a heading turns decorative. Most of these mistakes are small; the reason they matter is that they compound.

Clearer writing helps readers. Clearer structure helps AI systems interpret content more reliably. The point of an editorial handbook like this is not to rank higher, to promise citations, or to hit a magic number. The point is better communication. Everything else — search visibility, machine interpretability, the trust of a returning reader — tends to follow from that, without needing to be promised.

If you want to see how the ideas in this handbook translate into a diagnostic score for a specific passage, paste it into the AI Readability Checker. The check runs entirely in your browser.