Before You Publish an AI-Assisted Article: A Checklist

November 11, 2026 · 22 min read

Review an AI-assisted article in five separate passes before publishing: check the facts, edit the voice, cut structural clutter, review images, and test the page. A text generator can produce smooth, grammatical paragraphs in seconds. That fluency can hide fabricated citations, repetitive sentences, long introductions, and irrelevant images. Each needs an editor's attention.

Publishing generated text without review puts reader trust and search visibility at risk. Language models predict likely word sequences from training data; they do not check those words against reality. A survey on hallucination in large language models describes how these systems produce confident assertions that contradict source documents or cite publications that do not exist. An unverified number or broken citation gives readers reason to doubt the rest of the article.

Writers, editors, and publishers can use separate review passes to concentrate on one kind of problem at a time. Checking a source requires different attention from listening to a sentence or spotting a broken layout. Trying to do all of that in one rushed read makes errors easier to miss.

The five-pass review

Use these five stages to keep each kind of check focused.

1. Pass 1: Check facts and references. Verify every named entity, statistic, date, equation, quotation, and source link against primary reference material.
2. Pass 2: Edit voice and tone. Remove robotic phrasing and defensive apologies. Vary sentence length and make clear judgments.
3. Pass 3: Check structure and pacing. Put the answer first, cut introductory filler, and give wandering arguments a clear order. Replace formulaic listicles with connected prose.
4. Pass 4: Review images and media. Confirm that every diagram or screenshot delivers clear information, remove decorative graphics, compress media files, and verify alternative text.
5. Pass 5: Polish the text and test the page. Read the text aloud, check rendered formatting on mobile screens, validate outgoing links, and test navigational routes.

Pass 1: Check facts and references

Check what the article says before working on how it sounds. After spending time smoothing transitions, adjusting cadence, and replacing adjectives, an editor hesitates to delete a paragraph even after discovering that its underlying statistic or technical claim is fabricated. Models combine familiar language patterns without verifying their statements: a reasonable-sounding paragraph can describe a historical event that never happened, include broken software syntax, or cite an invented scientific paper.

Step 1: Audit named entities, dates, and historical claims

Mark every proper noun, company name, product title, and date. Check each one against an official source:

• Check that named individuals actually hold the titles, affiliations, and roles attributed to them.
• Confirm that historical events, product launch dates, and regulatory decisions occurred in the sequence stated.
• Verify software package names, command-line arguments, and API endpoint names against current official documentation.
• Remove any claim that attributes a quote, study, or numerical finding to an institution if you cannot locate that institution's original release.

A familiar name does not make the statement accurate. Models often mix details from the biographies of two specialists in the same field.

Step 2: Validate statistics, percentages, and mathematical logic

Check the arithmetic as well as the source. Language models struggle with calculations and statistical dependencies: a draft might claim fifty percent growth while its raw numbers show a thirty percent decline.

• Trace every percentage, financial figure, and measurement back to the primary dataset.
• Re-calculate internal sums, ratios, and percentages manually using a calculator or spreadsheet.
• Check the scope of any reported metric. Confirm whether a statistic applies globally, regionally, or only to a narrow test cohort.
• Verify date boundaries on numerical claims. A figure valid in 2021 may be wildly inaccurate today.

If a draft makes a broad numerical claim without an identifiable source, delete the claim or replace it with a verifiable, documented observation.

Step 3: Inspect quotations and citations

Models frequently invent plausible quotes for public figures or researchers. They also combine topical keywords and journal names into convincing paper titles and fake academic URLs.

• Search the exact wording of every direct quotation. If the quote does not appear in a verified recording, transcript, or primary text, rephrase the thought into a paraphrase or remove it.
• Open every hyperlink in the draft. Confirm that the target URL resolves to an active HTTP 200 status code and that the linked page directly supports the assertion made in your text.
• Verify authors, publication dates, and journal names for every cited study.
• Remove any citation where the paper exists but the findings contradict your draft's summary.

Fact-checking table

Worked example: Checking facts and qualifications

Here is a draft passage about distributed caching:

Before: "Distributed caching slashes query latency for repetitive read requests by storing database responses in memory, completely eliminating wait times across all system workloads."

The draft claims that caching eliminates wait times across all workloads, overstating what memory caching can accomplish.

After: "Distributed caching reduces query latency for repetitive read requests by storing database responses in memory."

The revision removes the exaggerated claim that caching eliminates wait times across all workloads. It replaces promotional phrasing with a modest description of how storing database responses in memory reduces query latency for repetitive read requests.

Pass 2: Edit voice and tone

Once the facts check out, read for voice. Generated drafts often sound stiff because they repeat sentence patterns, use abstract words, and avoid making a clear judgment. Conversational chatter and apologetic disclaimers can also get between the reader and the point.

Step 1: Eliminate defensive disclaimers and personal throat-clearing

In an analysis of technical community publishing errors, moderation editors describe drafts that fail because authors apologize for possible mistakes or ask readers to go easy on them. Others open with long resumes and biographies. Both delay the useful instruction.

Readers want clear answers they can trust:

• Cut opening disclaimers such as "I am relatively new to this topic, so please excuse any errors" or "In this humble writeup, I hope to share a few thoughts."
• Remove biographical lists that do not directly substantiate the specific technical advice in the post.
• Eliminate sycophantic praise directed at the audience or platform.
• Cut passive corporate phrases such as "we are proud to present" or "it is worth taking a moment to appreciate."

State your findings plainly and let the research or testing support them. Boasting and artificial modesty give the reader little to work with.

Step 2: Replace overused abstract words

Some words turn up much more often in generated text than in human prose. A study of more than 15 million PubMed biomedical abstracts from 2010 to 2024 found sharp increases in certain style words after LLMs became widely available.

Look for repeated uses of these words and choose a concrete alternative:

• Replace "delve" or "delve into" with "examine," "inspect," "test," or "read."
• Replace "tapestry" or "rich tapestry" with "collection," "history," or "variety."
• Replace "testament" or "serves as a testament" with "shows," "demonstrates," or "proves."
• Replace "crucial," "pivotal," or "paramount" with "important," "necessary," or explain the practical consequence directly.
• Replace "beacon," "realm," "foster," "harness," and "elevate" with plain verbs that describe the actual physical or digital action.

Our catalog of AI writing signs covers more of these patterns.

Step 3: Break repetitive sentence length and cadence

Some drafts settle into sentences of similar length and structure. A long run of them can become tiring to read.

Check sentence lengths and openings as you read:

• Follow a long, condition-rich sentence with a short statement. A five-word sentence can add emphasis. A longer sentence provides space for nuance and exceptions.
• Check the opening word of every sentence in a paragraph. If three sentences in a row begin with "The," "This," or "In addition," vary the syntax.
• Strip out trailing participial clauses ending in "-ing" (such as "highlighting the need for care" or "fostering improved collaboration"). These tacked-on phrases give an illusion of depth while adding no meaning.
• Cut formulaic transitional connectors like "Furthermore," "Moreover," "Consequently," and "On the other hand" when the logical connection between paragraphs is already obvious.

For another way to catch repetitive rhythm, see the sister site's read-aloud editing guide.

Worked example: Editing voice

Here is a draft passage about web server architecture:

Before: "While I am certainly not an authority on web servers, it is crucial to delve into how Nginx manages incoming connections. Nginx uses a non-blocking event loop to handle concurrent connections, where a single worker process manages multiple network sockets without assigning a dedicated operating system thread to each client request. This architecture stands as a vibrant testament to modern engineering, highlighting the importance of non-blocking event loops while fostering seamless throughput for organizations navigating complex digital landscapes."

The apology delays the explanation. Words such as "crucial," "delve," "vibrant testament," "fostering," and "navigating complex digital landscapes" add praise around the technical description. The trailing phrase "highlighting the importance" adds no useful detail.

After: "Nginx uses a non-blocking event loop to handle concurrent connections. A single worker process manages multiple network sockets without assigning a dedicated operating system thread to each client request."

The revision cuts the opening apology and decorative praise. It preserves the factual description of how Nginx uses an event loop and worker processes to manage network sockets, without diluting the explanation with buzzwords.

Pass 3: Check structure and the opening

Now check the order of the article. Give the answer early, develop the explanation in a logical sequence, and stop when the reader has what they need.

Step 1: Enforce an answer-first lead

Many generated drafts take three to five paragraphs to reach the point. They define familiar concepts, explain the importance of the broad topic, or repeat the title. Cut that warm-up.

Apply the inverted pyramid structure:

• Put the central conclusion, actionable recommendation, or primary definition in the very first paragraph.
• Answer the specific search query that brought the reader to the page before introducing background history.
• Delete introductory sentences that announce what the article will do ("In this article, we will examine the five most common reasons...").
• Remove rhetorical questions that state the obvious ("Have you ever wondered how databases store records?").

If a reader closes your article after thirty seconds, the opening two paragraphs should still give them a clear, useful takeaway.

Step 2: Organize by task, not by broad outline

Language models often follow a school-report outline: introduction, history, benefits, challenges, summary. A practical guide needs an order that follows the work the reader is trying to do.

Arrange sections around the reader's tasks:

• Group sections chronologically by the steps the reader must take.
• Use explicit descriptive subheadings (## and ###) that indicate what action or decision occurs in that section.
• Avoid vague headings like "Overview," "Background," "Considerations," or "Looking Ahead."
• Ensure each section addresses one distinct problem without overlapping neighboring sections.

Step 3: Eliminate repetitive bullet lists and bold prefixes

Models generate vertical bulleted lists where every item begins with a bold label followed by a colon:

• Scalability: Improves system capacity.
• Reliability: Prevents system downtime.
• Maintainability: Simplifies code updates.

The bold label often repeats a noun already in the sentence, slowing the reader down. Turn those lists into paragraphs. Keep lists when they help someone follow a sequence, check requirements, or compare distinct options.

Step 4: Cut empty conclusions

Generated drafts almost always end with filler: "In conclusion" or "To summarize," a recap of the previous three headings, and an empty send-off such as "As technology continues to evolve, embracing these practices will ensure a bright future."

• Delete the entire conclusion if it merely restates what the reader just finished reading.
• Replace a generic summary with practical next steps: related technical tasks, diagnostic checklists, or links to companion resources.
• Never end with broad prophecies about future technological trends unless the article specifically reviews longitudinal forecast data.

Worked example: Restructuring an introduction

Here is a draft opening for an article about database indexing:

Before: "In today's fast-paced digital world, data is growing at an unprecedented rate across global enterprises. Modern applications rely heavily on relational databases to store this vital information. But how can developers ensure that their queries run smoothly without bogging down server performance? In this comprehensive guide, we will explore database indexing. To begin with, storage engines can help developers avoid sluggish full table scans and shorten query execution times by organizing data into ordered lookup structures. Furthermore, placing a B-tree index on foreign key columns that receive frequent queries provides noticeable improvements in read performance. However, teams must also account for an added write-latency cost, because every insert, update, and delete requires the system to update the index."

The paragraph opens with broad statements about data growth, a rhetorical question, and a formal guide announcement before reaching the technical explanation.

After: "Database indexes reduce query execution time by maintaining ordered lookup structures, eliminating the need for full table scans. Adding a B-tree index on frequently queried foreign key columns speeds up read performance, but increases write latency because the database must update the index during every insert, update, and delete operation."

The revision cuts the general background statements, the rhetorical question, and the guide announcement. It places the explanation of the lookup structure and the write-latency trade-off at the very beginning of the section.

Pass 4: Review images and media

Review every chart, screenshot, diagram, and other image. Each should explain something difficult, document a claim, or direct the reader's attention. Decoration alone is not enough.

Step 1: Remove decorative and generic illustrations

Publishing platforms often encourage an image every few hundred words. Without relevant screenshots or diagrams, editors frequently fill the space with generated stock art: glowing brains, robots at keyboards, neon circuit boards, floating icons, or uncanny figures. These images distract without explaining anything and make the article look cheap and automated. If a section does not need a visual explanation, readable typography and clear subheadings are enough.

Give each retained image a clear editorial purpose:

• Process diagrams illustrate multi-step architectural workflows, state transitions, or data flows that are difficult to grasp from text alone.
• Comparative visuals contrast two configurations, user interfaces, or design layouts side by side.
• Evidence can include verified benchmark charts, oscilloscope readings, terminal outputs, or system monitors that support a specific factual claim.
• Annotated screenshots guide a user through a complicated software interface where menu locations or configuration flags are not obvious.

Remove images that provide neither data nor instruction. Leaving clean space is better than adding a distraction.

Step 2: Optimize file formats, dimensions, and compression

Large media files slow the page, use up mobile bandwidth, and make readers less likely to stay.

• Convert raster images to modern compressed formats like WebP or AVIF.
• Size images to their maximum displayed container width rather than embedding multi-megabyte originals.
• Strip unnecessary EXIF metadata, camera tags, and GPS coordinates from uploaded image files.
• Compress static diagrams and screenshots so file sizes remain below 150 kilobytes whenever possible.

Step 3: Write accurate, functional alternative text

Accessibility standards require descriptive alternative text for every informative image. The W3C Web Accessibility Initiative tutorial on informative images explains that alt text should convey the image's meaning and function. Decorative details and repeated file names do not do that job.

• State the specific concept, data trend, or interface control shown in the image.
• Avoid starting alt text with "Image of" or "Picture showing." Assistive screen readers already announce the presence of an image.
• For charts and data graphs, summarize the main comparative trend and note the primary data points in the alt text or the surrounding body copy.
• Keep alt text concise, ideally between one and two complete sentences.

Image review table

Pass 5: Polish the text and test the page

Test the article as a web page. Check its layout, links, and accessibility after the prose is ready.

Step 1: Perform the read-aloud audit

Reading aloud makes you process each word in order. When reading silently on a screen, it is easy to skip missing prepositions, repeated articles, and awkward syntax.

• Read the entire draft out loud at normal conversational speed.
• Mark every sentence where you stumble, lose breath, or need to re-read a clause to understand its grammatical structure.
• Rewrite tangled sentences by breaking them into two shorter clauses.
• Listen for repeated vocabulary. If you notice the same adjective or verb three times within a single subsection, replace two occurrences with precise alternatives.

Step 2: Line-by-line grammar and active verb conversion

Check the grammar in each paragraph:

• Identify passive verb constructions ("was calculated by," "is considered to be") and convert them to active verbs ("calculated," "represents").
• Eliminate nominalizations, where a strong verb has been turned into a clumsy noun phrase. Replace "conduct an analysis of" with "analyze," "make an adjustment to" with "adjust," and "perform an execution of" with "execute."
• Verify subject-verb agreement across complex compound subjects and conditional clauses.
• Remove redundant doublets such as "basic fundamentals," "advance planning," "future prospects," and "completely finished."

Our guide to manual humanizing techniques includes exercises for tightening verbs.

Step 3: Validate link integrity and navigation routes

Broken links frustrate readers and harm navigation:

• Click every internal link in the draft to verify that it resolves to an active path on the site without triggering a 404 error.
• Check that relative URL links use proper forward slashes and exact slugs.
• Verify that every outside citation opens in a new tab or preserves reader context appropriately.
• Ensure the article is reachable from the site topic index and sitemap.

Step 4: Verify search engine alignment and real value

Search engines evaluate whether a page answers the searcher's question. Google guidance on creating helpful content calls for firsthand depth, original insight, and useful information. Compiling web summaries just to attract search traffic does not meet that standard.

Before publishing, ask:

• Does this article offer original analysis, firsthand test results, or unique editorial framing that competing search results lack?
• Would a reader consider this page authoritative enough to bookmark or cite in their own professional work?
• Does the article avoid unsupported superlatives like "the best tool on the market" or "the definitive guide"?

If the article only repeats what other sites have published, pause before publishing. Add experimental observations, code examples, or diagnostic tables that help the reader do the work.

Step 5: Test rendered presentation on mobile and desktop

Preview the rendered page on desktop and mobile before calling it finished. A local markdown editor or word processor can hide layout problems that appear only in rendered HTML:

• Inspect the rendered page on both a desktop browser and a mobile device viewport.
• Confirm that data tables scroll horizontally or adapt cleanly without breaking the viewport width.
• Check that subheadings remain clearly differentiated from body text in size, weight, and spacing, and that stylesheet margins do not collapse.
• Ensure that code snippets and inline code tags wrap properly without clipping text or extending past their containers.

The complete pre-publication checklist

Use this checklist to record which checks each draft has passed:

Four common mistakes when reviewing AI-assisted text

1. Relying on AI text detectors as proof of quality

A low score from an automated text detector does not mean a draft is accurate, clear, or ready to publish. These tools compare text predictability against training distributions using statistical heuristics based on language models; they do not check whether claims are true or reasoning works. Because they match statistical patterns rather than evaluate substance, they regularly produce false positives and false negatives. A carefully researched article edited by hand can trigger an artificial flag when its prose is formal, structured, and grammatically standard, while fluent nonsense passes through undetected. Our guide on why AI detector scores can mislead explains how these statistical tools operate. Judge a draft by its factual accuracy, clarity, and usefulness rather than a detector score.

2. Passing the draft through an automated humanizer

An automated humanizer or paraphrasing tool can make stiff prose worse. These tools use statistical synonym swaps and clause inversions that frequently change technical meaning, introduce odd vocabulary, or remove conditions. "Caching reduces latency when the hit rate exceeds eighty percent" can become "caching drops lag during common operations." The condition that made the claim useful has disappeared. Edit with a specific purpose and check what each change does to the meaning.

3. Stripping necessary technical qualifications

Shorter sentences can lose necessary conditions. "Docker containers isolate processes" is simpler than "Docker containers isolate processes using Linux namespaces and control groups, but share the host kernel." For an article about security boundaries, the shared kernel matters. Cut empty wording while keeping every condition, constraint, and qualification that determines how the system behaves.

4. Forcing artificial casualness and slang

Adding slang, internet idioms, or deliberate punctuation mistakes does not make a draft more convincing. Forced banter can alienate readers of professional, technical, or educational work. A formal technical manual can sound human through firsthand observations, useful troubleshooting advice, and realistic accounts of a tool's limits. Choose the tone your readers need.

Frequently asked questions

How long should an editorial audit take for an AI-assisted article?

For a standard article of 2,000 to 3,000 words, a thorough five-pass audit typically takes between 90 minutes and three hours. The time depends on how technical the subject is and how many claims need checking against primary sources. Allow extra time to test code or mathematical formulas in a sandbox. Rushing leaves less room for those checks.

Should I disclose that an article was drafted with AI assistance?

Follow your publication's, employer's, or industry regulator's editorial guidelines. Many academic journals, technical platforms, and media organizations require disclosure when generative models help with drafting or research. The human author and editor remain responsible for the article's legal, factual, and ethical content. Blaming a tool provides no defense for defamatory statements, copyright infringement, or dangerous technical advice.

What is the most common reason AI-assisted articles fail to perform in search?

They usually lack original information and practical depth. Search engines look for value beyond what is already available. Most raw AI drafts summarize existing web consensus without firsthand knowledge that answers a specific question. Without new data, case studies, benchmark tests, or expert troubleshooting, there is little reason to rank the page above established resources.

When should I delete a generated draft and start over from scratch?

Start again if Pass 1 shows that the central argument depends on false premises, imaginary software features, or fabricated research. Repairing that argument may take more effort than writing from your notes and firsthand experience. If you have to replace most of the draft to correct its facts, work from primary documentation instead.

How do I handle external links when the model provides no citations?

Look for the original peer-reviewed paper, official documentation, or institutional report behind the claim. Attaching a random blog link does not verify it. If you cannot find an authoritative primary source, remove the claim or describe it as an unverified observation from your own testing. Each outside link should lead to a credible, permanent source that you have checked.