This skill has two parts. Part 1 describes how good nonfiction texts are structured, i.e., texts that readers actually read, save, and whose author they remember. Part 2 describes which typical AI patterns are to be avoided.
Both belong together: A text that only avoids AI patterns is not automatically good. And a text that is good in content fails if it sounds like a language model.
Part 1: How good nonfiction texts work
The opening (hook)
The first sentence decides whether someone keeps reading. Good hooks are factually correct and spark curiosity. Invented stories as an opening are forbidden because they destroy credibility and are recognized as AI patterns ("Imagine it's 6 a.m. in a factory hall...").
Six proven hook types that must be varied:
1. Counterintuitive statement "Most shift supervisors print out their KPIs on paper in the morning. Not because they reject technology, but because their MES has no usable morning view."
2. Surprising number or statistic "92% of Excel files in production planning contain at least one formula error (Panko, 2008)."
3. Concrete scene (real, not invented) "In last week's audit, 14 of 200 batch records were missing. All from the same shift."
4. Direct question "When did you last check whether your OEE calculation includes micro-stops?"
5. Quote from a real person "'We evaluated three MES systems. All of them could do everything. None of them could do what we really needed.' (Production manager, mid-sized company, 2024)"
6. Contradiction or tension "Companies invest millions in traceability. At the same time, 40% of tracebacks run via Outlook emails."
Not every text needs a dramatic hook. For short technical texts, instructions, or status updates, a clear, direct first sentence that immediately says what it is about is enough.
The orientation (nut graf / summary)
After the hook, the reader must know within the first three paragraphs:
- What exactly is it about?
- Why is it relevant to them?
- What can they expect in the rest of the text?
For longer texts (from about 800 words), a summary belongs at the beginning. Not as a dry list, but as a compact paragraph that anticipates the core statement. That is not a sign of indecision ("I'm already giving everything away"), but respect for the reader's time. Anyone who reads the summary and thinks "that's enough for me" has still taken something away. Anyone who wants more reads on.
Example of a good summary: "This article shows why classic OEE calculations in practice are often off by 5 to 15 percentage points, which three sources of error are the most common, and how to fix them without new tooling. Reading time: 6 minutes."
Surprising facts and measured humor
Surprising facts activate the dopamine reward system and promote long-term memory formation (Edutopia, based on neuroscience studies). A good nonfiction text sprinkles in a surprising piece of information every 300 to 500 words that the reader did not expect.
Humor works in nonfiction texts when it arises organically from the subject. Forced humor is harmful. Good forms:
- Dry understatement ("The spreadsheet had 47 tabs. The documentation consisted of a Post-it.")
- Self-deprecation ("Yes, I once misused a pivot table as a database too.")
- Absurd but true details ("The server had been running since 2011. Nobody knew the password, but it kept running.")
Bad forms:
- Puns that stop the reading flow
- "Imagine" scenarios
- Sarcasm about the reader or their field
Specific details instead of abstraction
The strongest lever for memorable texts is intimate, specific details that the reader would not know without the author. That is the difference between "production was inefficient" and "the shift supervisor printed out 14 pages of Excel every morning, highlighted three rows in yellow, and threw away the rest."
Specific details create images in the mind. Abstract statements create nothing.
| Abstract (bad) | Specific (good) |
|---|---|
| "Digitalization is progressing." | "Since January, the shift handover has been done via a tablet instead of the blue notebook." |
| "AI can optimize processes." | "The algorithm found out that machine 7 takes 12 minutes longer than necessary after every cleaning." |
| "Many companies have problems with data quality." | "In the sample, 23% of the batches were missing the temperature reading at the second hardening step." |
Evidence and source work
Depending on the depth of the text, evidence must take different forms:
| Text type | Form of evidence |
|---|---|
| LinkedIn post, blog (short) | Individual figures with a source note in the text |
| Trade article, whitepaper | Inline references, bibliography at the end |
| Technical documentation | Norms, standards, version numbers |
Unsupported claims are unacceptable in technical texts. If a figure or statement cannot be substantiated, it must be labeled as an estimate, empirical value, or assumption. "In my experience" is more honest than a made-up statistic.
Technical terms and industry-standard abbreviations belong in technical texts, because they signal competence and save space. Explain them on first use, then use them freely. Example: "Overall Equipment Effectiveness (OEE) measures ... In the following, I will refer to OEE."
Text rhythm and structure
Good nonfiction texts have a deliberate rhythm:
Vary sentence length. Short sentences create pace. Longer sentences are suitable for contexts that should not be squeezed into three words, because otherwise the reader loses the thread. Variety keeps them awake.
Vary paragraph length. A paragraph may have two sentences. Another seven. Uniformity is the opposite of readability.
Subheadings as orientation. Headings should be plain and say what is coming. Not: "The revolution of data-driven manufacturing". But rather: "How data collection works".
Transitions between sections. A section should not end abruptly and the next should not begin without a connection. One sentence that bridges the gap is enough.
Limitations and honesty
Texts that mention only advantages come across as advertising. Texts that admit weaknesses, name uncertainties and mark boundaries come across as authentic and stay in the mind.
"This works well for runs of 500 units or more. Below 100, the effort is not worth it." Sentences like that build trust.
Part 2: Avoiding AI patterns
Forbidden stylistic devices
Em dashes are forbidden. No em dash anywhere in the text. Neither as an insertion nor as a substitute for a colon or semicolon. Since 2024, em dashes have been regarded in public perception as an AI signal. GPT-4o uses around ten times more em dashes than its predecessor. Whether the perception is linguistically correct does not matter. Readers react to it. So: period, comma, semicolon, colon, parentheses. That is enough.
Invented opening stories are forbidden. No "Imagine", no "It is Monday, 6 a.m. in a factory hall", no narrative opening with fictional people. If an example forms the opening, it must be real or marked as hypothetical.
Invented anecdotes in the running text are forbidden. No "One plant I worked with", no "A company I know", no "I've seen cases where". LLMs routinely invent concrete-sounding examples to support statements. These pseudo-anecdotes are a strong AI signal. Instead: use general, verifiable statements ("Weekend standby consumption in manufacturing plants is often 20 to 40 percent of production consumption") or cite real sources. If the author actually has a real example, it must be so specific that it cannot sound invented (company name, place, year, context).
Overused words (AI vocabulary)
These words have appeared significantly more often in AI-generated texts since 2023:
| Avoid | Instead |
|---|---|
| delve, dive into | examine, look at, consider |
| crucial, pivotal, vital | important, relevant, central |
| landscape (metaphorical) | area, environment, situation |
| foster, bolster | support, strengthen |
| harness, leverage | use, employ |
| multifaceted | complex, multilayered |
| comprehensive | comprehensive, complete |
| underscores, highlights | shows, makes clear |
| testament to | proof of, shows |
| realm | area, domain |
| tapestry, synergy | delete, usually superfluous |
| it's important to note | delete |
| in conclusion | delete or: in short |
| game-changer | delete or name the concrete advantage |
| revolutionize | delete or describe the concrete effect |
| seamlessly | delete |
| robust (outside of technical contexts) | delete or phrase more precisely |
Dramatic transition phrases (AI rhetoric)
LLMs produce typical rhetorical transitions that rarely occur in human specialist texts. These phrases are strong AI signals:
English (forbidden):
- "And that is the part nobody talks about..."
- "Here's the tension though."
- "The gap is not in X. The gap is in Y." (mirrored sentence structure as the punchline)
- "Here's the thing."
- "Let that sink in."
- "And here's why that matters."
- "But here's where it gets interesting."
- "The short answer is... The long answer is..."
German (forbidden):
- "Und genau das ist der Punkt, den niemand anspricht..."
- "Hier wird es spannend."
- "Das Problem ist nicht X. Das Problem ist Y."
- "Und das hat Konsequenzen."
Instead: omit transitions or replace them with a normal sentence that introduces the next thought. Not every section needs a dramatic opening.
Rhythmic repetition as a pseudo-punchline
LLMs use rhythmic sentence repetition to make texts seem "snappy." The same sentence pattern is applied three or four times in a row, each time with different content:
Forbidden patterns:
- "Das ist eure Baseline." / "Das ist Cash." / "Das ist Scope 2." (same sentence structure as a rhetorical hammer)
- "That's your energy data. That's your compliance. That's your competitive edge."
- Any variation of "short statement + one-line comment" that repeats more than twice in a row
This pattern stands out because human authors rarely use the same rhetorical trick three times in a row. Once or twice it can work. From the third time on, it is a pattern, not a stylistic device.
Instead: Vary sentence structures. If a short commentary sentence works well, use it once and then change the structure.
Confrontational tone as an anti-AI signal (optional)
LLMs write neutrally, in a balanced and cautious way by default. That is correct in many contexts (specialist publication, technical documentation). But in contexts like Reddit, LinkedIn posts, industry blogs, or opinion pieces, this neutrality feels artificial.
If the context allows it, a confrontational, opinionated tone is a strong signal of human writing:
- Direct criticism ("Most ESG consultants sell colorful PDFs with no substance")
- Provocative theses ("Anyone who sweats over the ESG report has failed at digitalization")
- Simplifications intended to provoke discussion (deliberately sharpened, not untrue)
- Colloquial language and industry jargon instead of formal language
This is NOT a license for polemics without substance. The sharpness must be substantively backed up. But: a text that provokes no one will also be shared by no one.
This device is optional and context-dependent. For technical documentation or a whitepaper, it would be out of place. For a Reddit post in r/manufacturing, it is exactly right.
Inflated phrases
Delete these formulations or replace them with the direct statement:
- "This isn't just about X. It's about transformation."
- "X continues to redefine the landscape."
- "A testament to the power of Y."
- "One of the most important things to consider is..."
- "In today's fast-paced world..."
- "It's worth noting that..."
- "Let's dive in."
- "But here's the thing..."
- "Without further ado..."
Emphasis Crutches
Empty intensifiers that signal importance without delivering it. Delete.
- "Full stop." / "Period." / "Punkt."
- "Make no mistake" / "Keine Frage"
- "This matters because" / "Das ist wichtig weil"
Business jargon
| Avoid | Instead |
|---|---|
| navigate (challenges) | handle, address / angehen, bearbeiten |
| unpack (analysis) | explain, examine / erklaeren, untersuchen |
| lean into | accept, embrace / annehmen, akzeptieren |
| double down | commit, increase / sich festlegen, verstaerken |
| deep dive | analysis, examination / Analyse, Untersuchung |
| take a step back | reconsider / ueberdenken |
| moving forward | next, from now / als naechstes, ab jetzt |
| circle back | return to, revisit / zurueckkommen auf |
| on the same page | aligned, agreed / abgestimmt, einig |
Meta-Commentary (self-reference)
Texts that talk about themselves instead of moving forward. Delete.
- "Hint:" / "Plot twist:" / "Spoiler:"
- "You already know this, but" / "Du weisst das schon, aber"
- "But that's another post" / "Aber das ist ein anderes Thema"
- "X is a feature, not a bug"
- "The rest of this essay explains..." / "Im Folgenden erklaere ich..."
- "Let me walk you through..." / "Lass mich dich durchfuehren..."
- "In this section, we'll..." / "In diesem Abschnitt werden wir..."
- "As we'll see..." / "Wie wir sehen werden..."
- "I want to explore..." / "Ich moechte untersuchen..."
Telling instead of Showing
Asserting importance or difficulty instead of showing it. Cut or replace with a concrete example.
- "This is genuinely hard" / "Das ist wirklich schwierig"
- "This is what leadership actually looks like" / "So sieht Fuehrung wirklich aus"
- "actually matters" / "wirklich wichtig ist"
Vague Declaratives
Sentences that assert significance without naming the concrete content. Either cut them or name the concrete thing.
- "The reasons are structural" / "Die Gruende sind strukturell"
- "The implications are significant" / "Die Auswirkungen sind erheblich"
- "This is the deepest problem" / "Das ist das tiefste Problem"
- "The stakes are high" / "Es steht viel auf dem Spiel"
- "The consequences are real" / "Die Konsequenzen sind real"
Adverbs and Softeners
Question categorically all -ly adverbs. Most are filler. Always cut these specific words:
| English | German |
|---|---|
| really, just, literally | wirklich, einfach, buchstaeblich |
| genuinely, honestly, simply | aufrichtig, ehrlich gesagt, schlicht |
| actually, deeply, truly | tatsaechlich, zutiefst, wahrlich |
| fundamentally, inherently | grundsaetzlich, von Natur aus |
| inevitably, interestingly | unweigerlich, interessanterweise |
| importantly, crucially | wichtigerweise, entscheidenderweise |
As well as these filler phrases:
- "At its core" / "Im Kern"
- "At the end of the day" / "Am Ende des Tages"
- "When it comes to" / "Wenn es um ... geht"
- "In a world where" / "In einer Welt in der"
- "The reality is" / "Die Realitaet ist"
Symmetrical Argumentative Arcs (LLM Outline Pattern)
LLMs almost always produce the same text architecture: present the problem, explain the solution, incorporate counterarguments, propose a pragmatic middle ground, disclose bias. This sequence is so predictable that it alone suffices as an AI signal. A human author jumps, digresses, sets emphases arbitrarily, leaves things out.
Rules for text architecture:
- Not every section needs a symmetrical counterpart. If you write "advantages," you do not necessarily need "disadvantages" as the next section.
- Sections may be of different lengths. A section with 3 sentences next to one with 12 sentences is normal. Evenly portioned sections are an AI signal.
- The order of the arguments may be unconventional. Instead of problem-solution-limitation, sometimes start with the limitation. Or put the strongest point in the middle instead of at the end.
- Digressions and side remarks are allowed and desirable. Humans write with more abrupt shifts than LLMs. A thought that only half fits the topic but is interesting makes a text more human.
- Not every section needs an intermediate heading. Some thoughts flow better into one another without formal separation.
- Avoid the pattern "X has advantages and disadvantages, the truth lies in the middle". That is the default output of every LLM text and immediately recognizable.
- Avoid perfectly symmetrical heading pairs like "Why skeptics have a point" / "Why they'll still need it". Humans structure things more asymmetrically.
Avoid broad generalist perspective
LLMs reflexively cover as many aspects of a topic as possible: technology, finance, recruiting, regulation, all in one article. That comes across like a Wikipedia entry, not like a specialist writing about their area of expertise.
Rules:
- An article has one focus. Not three. If the topic is ESG data on the shop floor, then the focus is the data, not also recruiting and bank conditions.
- Peripheral topics may be mentioned in one sentence, but not in their own paragraph.
- Ask yourself: Would a single specialist cover all of this in one text? If not, cut the side shows.
- Depth beats breadth. Better to explain one technical matter thoroughly than to touch on five topics.
Plausible numbers without sources (tightened rule)
LLMs generate realistic-sounding numbers without real sources. "40 to 60 percent", "$29,000 per employee", "0.3 to 0.8 percentage points" sound plausible, but are often hallucinated or imprecisely assembled from training data. A human expert author would write: "According to study X by institution Y (year)".
Tightened rules:
- Every number that supports a claim needs one of the following labels:
- Real source (study, report, institution, year)
- Explicit labeling as an estimate ("in my experience this is around...", "industry estimates assume...")
- Derivation ("at 200 kWh per shift and 250 working days, this gives...")
- Numbers without any classification are forbidden. "20 to 40 percent" without context is an AI signal.
- Better fewer numbers with real sources than many numbers without evidence. Three substantiated numbers are stronger than ten unsubstantiated ones.
- When in doubt, leave out the number and formulate the statement qualitatively.
Credibility wrapper and bias disclaimer
At the end of texts, LLMs routinely insert a paragraph that relativizes their own perspective: "I should disclose that I work in X, so I have a professional interest in Y. This bias is worth naming." At first glance this sounds honest, but it is a typical LLM pattern because it is appended mechanically, without real substance.
Rules:
- No dedicated "honest caveat" or "disclosure" paragraph at the end. If the author has a bias, they should mention it in passing in the text, not as a formal disclaimer.
- No "I work in X, so take this with a grain of salt". Instead: make the author's perspective clear through the way they write.
- Limitations belong where they are relevant to the content, not as a summarized paragraph at the end.
- The author tagline at the end (e.g. "I've spent 15 years in X") is okay, but without the relativizing paragraph before it.
Structural AI patterns
| Problem | Solution |
|---|---|
| Rule of three (always 3 bullet points) | Vary: sometimes 2, sometimes 4, sometimes no list |
| Uniform paragraph lengths | Deliberately make paragraphs different lengths. Specifically: at least one paragraph with 1-2 sentences and at least one paragraph with 6+ sentences per 500 words |
| Excessive bullet points | Prefer prose |
| Inflated headings | Plain subheadings |
| Every section ends with a summary | Omit summaries |
| Every paragraph begins with a transition | Sometimes start directly |
| All paragraphs 3-6 sentences, similar sentence length, same tone | Deliberately break the rhythm: a two-liner, then a long block, then a one-liner |
Structural sentence patterns (extended)
The following patterns are statistically overrepresented in AI-generated texts. Individually they seem harmless, but in combination they reveal their origin.
Binary contrasts
The pattern "Not X. But Y." or "The answer isn't X. It's Y." creates artificial drama. Instead: name Y directly.
| Avoid | Instead |
|---|---|
| "Not because X. Because Y." | "Because Y." |
| "It's not about X. It's about Y." | "It's about Y." |
| "The question isn't X. It's Y." | "The question is Y." |
| "The answer is not X. The answer is Y." | "The answer is Y." |
| "stops being X and starts being Y" | Directly describe what happens |
| "stops being X and becomes Y" | Directly describe what happens |
Negative listing
Listing what something is NOT before saying what it IS. The reader doesn't need the run-up.
| Avoid | Instead |
|---|---|
| "Not an X. Not a Y. A Z." | "A Z." / "Ein Z." |
| "It was not an X. It was not a Y. It was Z." | "It was Z." |
Dramatic Fragmentation
Sentence fragments as a stylistic device come across as artificial depth.
| Avoid | Instead |
|---|---|
| "Trust. That's it. That's the thing." | Write a complete sentence |
| "Trust. Nothing more. That's all." | Write a complete sentence |
| "X. And Y. And Z." | Normal sentence with conjunctions |
| "This unlocks something. [Single word]." | Formulate the statement in one sentence |
Rhetorical Setups
These phrases announce an insight instead of delivering it.
| Avoid | Instead |
|---|---|
| "What if [Reframe]?" | Formulate the reframe directly as a statement |
| "What if [Reframe]?" | Formulate the reframe directly as a statement |
| "Here's what I mean:" | Delete, continue writing directly |
| "Think about it:" / "Denk mal drueber nach:" | Delete |
| "And that's okay." / "Und das ist in Ordnung." | Delete, the reader does not need permission |
False Agency
AI gives inanimate things human verbs in order not to have to name the actor.
| Avoid | Instead |
|---|---|
| "the decision emerges" | "the team decided" |
| "die Entscheidung entsteht" | "das Team entschied" |
| "the market rewards" | "buyers pay for" |
| "der Markt belohnt" | "Kunden kaufen" |
| "the data tells us" | "we concluded from the data" |
| "die Daten zeigen uns" | "wir schliessen aus den Daten" |
| "the culture shifts" | "people changed their behavior" |
| "die Kultur veraendert sich" | "die Mitarbeiter aenderten ihr Verhalten" |
Rule of thumb: If a subject in the sentence cannot physically do anything, the actual actor is missing.
Narrator-from-a-Distance
AI writes like an omniscient observer instead of putting the reader into the scene.
| Avoid | Instead |
|---|---|
| "Nobody designed this." | "You didn't sit down and design this." |
| "Niemand hat das so geplant." | "Du hast dich nicht hingesetzt und das geplant." |
| "This happens because..." | "You see this when..." |
| "Das passiert weil..." | "You notice this when..." |
| "People tend to..." | "You probably..." |
| "People tend to..." | "You probably know this..." |
Passive Voice (Passive Constructions)
Passive hides the actor and drains energy from the sentence.
| Avoid | Instead |
|---|---|
| "X was created" / "X wurde erstellt" | Who created it? Name them. |
| "It is believed that" / "Es wird angenommen" | Who assumes that? Name them. |
| "Mistakes were made" / "Fehler wurden gemacht" | Who made the mistakes? Name them. |
| "The decision was reached" / "Die Entscheidung wurde getroffen" | Who decided? Name them. |
Wh-Sentence Openers as Crutches
Sentences that begin with What, When, Where, Which, Who, Why, How become a crutch when they pile up.
| Avoid | Instead |
|---|---|
| "What makes this hard is..." | "The constraint is..." / "Die Einschraenkung ist..." |
| "Was das schwierig macht ist..." | Name the constraint directly |
| Paragraphs that begin with "So" | Begin with content |
| Sentences that begin with "Look," | Delete |
Tonal AI Patterns
| Problem | Solution |
|---|---|
| Validation patterns ("That is understandable", "Good question") | Get straight to the point |
| Exaggerated enthusiasm | Sober, factual |
| Avoidance of friction (no problems, everything smooth) | Mention difficulties |
| Perfect smoothness | Allow rough edges |
| Patronizing explanatory tone | Write at eye level |
Formatting
| Problem | Solution |
|---|---|
| Excessive boldface | Use sparingly |
| Markdown artifacts (asterisks, underscores) | Remove |
| Title Case in German headings | Capitalize only the first word |
| Too many bullet points | Prefer prose |
Part 3: Scoring Before Submission
Score the finished text on these 5 dimensions, each from 1-10 points:
| Dimension | Check question | 1 (poor) | 10 (good) |
|---|---|---|---|
| Directness / Direktheit | Do statements stand there, or are they announced? | Every paragraph has a run-up | Every sentence delivers immediately |
| Rhythm / Rhythmus | Do sentence and paragraph lengths vary? | Everything the same length, monotonous | Deliberate switch, vivid |
| Trust / reader trust | Is the reader trusted to think along? | Everything is explained and justified | Facts stand, reader draws conclusions |
| Authenticity / authenticity | Does the text sound like a human? | Immediately recognizable as AI | No AI signal detectable |
| Density / density | Is every word necessary? | Lots of filler material, bloated | Nothing can be cut without loss |
Target score: 35 out of 50 points.
Below 35: rework. Start with the dimension that has the lowest score.
Quick checks (quick review before submission):
Go through this list. Every "yes" requires a correction:
- Does the text contain adverbs? Cut them.
- Passive constructions? Find the actor, make them the subject.
- Does an inanimate thing perform a human action? Name the person.
- Does the sentence begin with What/When/Where/Who/Why/How and do they pile up? Restructure.
- "Here's what/this/that" run-up? Get to the point.
- "Not X, it's Y" contrast? Name Y directly.
- Three consecutive sentences of the same length? Break one.
- Does the paragraph end with a punchy one-liner? Vary it.
- Em dash anywhere? Remove it.
- Vague statement without concrete content? Make it concrete or cut it.
- Narrator's voice from a distance? Put the reader in the scene.
- Meta-commentary ("In the following...", "Let me walk you through...")? Cut it.
Checklist before publication
Content and structure:
- Hook: Is the opening one of the six permitted types? No invented story?
- Summary: Present for texts of 800 words or more?
- Focus: Does the text have ONE main focus, not five secondary topics?
- Architecture: Is the section sequence NOT the standard LLM pattern (problem-solution-counterargument-middle ground-disclaimer)?
- Asymmetry: Are sections of different lengths? No symmetrical heading pairs?
- Surprise: At least one surprising fact every 300 to 500 words?
- Details: Concrete, specific examples instead of abstraction?
- Honesty: Limitations where they belong in terms of content, NOT as a blanket disclaimer at the end?
Evidence: 9. Does every number have a source OR is it marked as an estimate/empirical value? 10. No "plausible-sounding" numbers without any context? 11. No invented anecdotes ("One plant I know", "A company I worked with")?
Linguistic AI signals: 12. Dashes: Not a single em dash in the text? 13. AI vocabulary: No words from the avoidance list? 14. Dramatic transitions: No AI rhetoric ("Here's the tension", "And that's the part nobody talks about")? 15. Mirrored sentence structures as a punchline avoided ("The gap is not in X. The gap is in Y.")? 16. No rhythmic repetition (same sentence structure 3+ times in a row)?
Rhythm and format: 17. Sentence lengths: Deliberately varied (not everything 15-20 words)? 18. Paragraph lengths: Deliberately varied (at least one two-liner and one 6+ sentence block)? 19. Bullet points: Reduced to the bare essentials, prose preferred? 20. Headings: Plain and direct? 21. Tone: Like a competent expert, not like a PR agency? On Reddit/LinkedIn, deliberately confrontational if appropriate?
Meta-check: 22. Would a single human expert author write this text this way? Or does it cover too many areas at once? 23. No credibility wrapper at the end ("I should disclose my bias...")?
Stop-slop checks: 24. Scoring: Does the text reach at least 35/50 points in the scoring (Part 3)? 25. False agency: No lifeless subject performs a human action? 26. Passive voice: Is the actor named everywhere? 27. Meta-commentary: No self-reference ("In this section...", "Im Folgenden...")? 28. Business jargon: No navigate, unpack, lean into, double down, deep dive? 29. Vague declaratives: No sentences that assert meaning without concrete content? 30. Adverbs: No unnecessarily intensifying adverbs (really, just, genuinely, actually)?
Sources
- Wikipedia: Signs of AI Writing (August 2025)
- WikiProject AI Cleanup
- Studies on AI vocabulary frequency (2023-2025)
- Nieman Storyboard: Nut Grafs (2021)
- Poynter: The Nut Graf (2003)
- Plagiarism Today: Em Dashes and AI Writing (2025)
- The Conversation: Spotting AI Text (2025)
- British Academy Book Prize jury criteria (2025)
- Panko, R.: Spreadsheet Errors (2008)
- Edutopia: Humor Boosts Retention (neuroscientific basis)
- Practical feedback: Stylistic AI analysis of an ESG specialist article (March 2026), identified six detection patterns: symmetrical argument arcs, uniform paragraph lengths, dramatic transition phrases, plausible numbers without sources, credibility wrappers, broad generalist perspective
- hardikpandya/stop-slop (GitHub, MIT license, 2025)