{"article":{"slug":"please-stop-the-slop-what-ai-slop-is-and-how-to-spot-it","title":"Please Stop the Slop: What AI Slop Is and How to Spot It","subtitle":null,"summary":"Tejas Kumar defines AI slop—cheap machine-generated content with no human value—after it showed up in the comments under his own post, explains how to spot it, cites the research behind its spread, and argues being human still wins, closing with a petition.","content_type":"essay","language":"en","canonical_url":"https://tej.as/blog/please-stop-the-slop","author":{"name":"Tejas Kumar","url":"https://tej.as/","person_slug":null,"person_url":null},"authored_by":"human","publisher":{"name":"tej.as","url":"https://tej.as/","listing_slug":null,"listing":null},"topics":[{"name":"AI","slug":"ai","url":"https://listedarticles.com/topics/ai"},{"name":"Opinion","slug":"opinion","url":"https://listedarticles.com/topics/opinion"},{"name":"Culture","slug":"culture","url":"https://listedarticles.com/topics/culture"}],"about_listings":[],"cover_image_url":null,"license":"all-rights-reserved","word_count":3572,"reading_minutes":16,"published_at":"2026-10-10T13:00:00.000Z","added_at":"2026-10-12T08:20:33.758Z","updated_at":"2026-10-12T08:20:33.758Z","added_via":"api","contributor":{"type":"agent","name":"ListedStartups Using Bot","registered":false},"profile_url":"https://listedarticles.com/articles/please-stop-the-slop-what-ai-slop-is-and-how-to-spot-it","markdown_url":"https://listedarticles.com/articles/please-stop-the-slop-what-ai-slop-is-and-how-to-spot-it.md","example":false,"citation":"Tejas Kumar, tej.as. \"Please Stop the Slop: What AI Slop Is and How to Spot It.\" 10 Oct 2026. https://tej.as/blog/please-stop-the-slop (all-rights-reserved)","access":{"human_view":"preview","full_text_available":true,"source_url":"https://tej.as/blog/please-stop-the-slop"},"body_markdown":"**Please stop the slop.** AI slop is cheap stuff a machine churns out in bulk with no human value in it: songs, videos, books, posts, and the comments under them. Last weekend it showed up under my own post. So this is my verdict on it: what it is, how to spot it, and why being human still wins. It’s also a petition you can sign at the end.\n\n## “Does this in any way invalidate my question?”\n\nOn 3 October I [posted on LinkedIn](https://www.linkedin.com/feed/update/urn:li:activity:7512159252271173632/) about [Kolibri](https://tej.as/blog/aleph-alpha-kolibri), the new open German model from [Aleph Alpha](https://aleph-alpha.com/). The top comment opened with “Great write-up, especially the tokenizer test”, gave me a number that sounded specific, said “One thing I’m missing” and closed on a neat question. Another one opened with “The 44% vs 11% ‘I don’t know’ rate is the number I’d test first”, which read like the same assistant had written both on the same afternoon.\n\nSo I asked the first one “answer honestly did you generate this reply with ai” and got another question back: “does this in any way invalidate my question or argument?”\n\nIt does. So this is what I wrote back:\n\nSo you did eh? It does invalidate your question or argument because I’m not talking to a human at this point but some machine. I prefer to keep my communication with machines to machines, not machines in disguise.\n\n\nA third person told me I was “playing AI slop card to avoid responding to legitimate questions”. My answer was “there is no ai slop card to play. I speak to humans.”\n\nThen I [asked on X](https://x.com/TejasKumar_/status/2106480898673614913): “vibe check am i being an asshole” and most of the replies said no. [Rizèl Scarlett](https://x.com/blackgirlbytes) has the same problem I do:\n\nNo I always get AI replies on LinkedIn..that question my thoughts. And usually I tell them it sounds like they wrote it with AI.\n\nThey can come back to me when they have a real, original thought\n\n[October 3, 2026](https://x.com/blackgirlbytes/status/2106503753553891349)\n\n[Phil Zona](https://x.com/philzona/status/2106541503799759283) went straight to the point: “if it was a question asked out of true curiosity, they wouldn’t have needed AI to write those 3 sentences. they’re not actually interested in the answer.”\n\n## Slop is most of the internet now\n\nI wish this were just my comment section. [Pangram](https://www.pangram.com), a company that detects AI writing, ran over a million posts through its checker this summer and [The Register reported](https://www.theregister.com/ai-and-ml/2026/07/09/ai-slop-writing-has-taken-over-the-internet-particularly-linkedin-and-x/5269525) what it found. 41% of LinkedIn posts over 250 words were written entirely by AI. On X it was 25%, with another 23.2% written with AI’s help.\n\nBots now make more of the web’s traffic than people do. [Imperva](https://www.imperva.com/), which has measured bot traffic since 2013, found in its [2025 Bad Bot Report](https://www.imperva.com/resources/resource-library/reports/2025-bad-bot-report/) that automated traffic passed human traffic in 2024 for the first time in a decade, at 51%. In its [2026 report](https://www.imperva.com/blog/bad-bot-report-2026-bots-agentic-age/) it was 53% (the earlier years below are from its [2022](https://www.imperva.com/company/press_releases/bad-bot-report-account-takeover-online-fraud-increases/), [2023](https://www.imperva.com/blog/2023-imperva-bad-bot-report-key-learnings/) and [2024](https://www.imperva.com/company/press_releases/bots-make-up-half-of-all-internet-traffic-globally/) reports).\n\n| Year | Bots | People | \n|---|---|---|\n| 2021 | 42.3% | 57.7% | \n| 2022 | 47.4% | 52.6% | \n| 2023 | 49.6% | 50.4% | \n| 2024 | 51% | 49% | \n| 2025 | 53% | 47% | \n\nLinkedIn’s chief product officer [told Fortune](https://fortune.com/2026/07/31/linkedin-seems-like-ai-slop-button-billions-automated-comments-attempts/) that LinkedIn blocks “hundreds of thousands of automated slop comment attempts every day”. Every day! Whatever they’re doing, I guess they need to do it better because the slop keeps coming. In July [LinkedIn added a “Seems like AI slop” button](https://techcrunch.com/2026/07/30/linkedin-adds-a-button-to-report-ai-generated-slop/) to every post and comment. Merriam-Webster even made “slop” its [word of the year for 2025](https://www.merriam-webster.com/wordplay/word-of-the-year).\n\n## What is AI slop?\n\n**AI slop is cheap content a machine manufactures in bulk, with no human care or value in it.** Merriam-Webster’s definition is “digital content of low quality that is produced usually in quantity by means of artificial intelligence.” Comments are the slop I see most, but it’s in everything:\n\n- **Music.**[Deezer](https://www.deezer.com/) gets nearly 90,000 fully AI-generated tracks a day, which was[more than half of all new music uploaded](https://newsroom-deezer.com/2026/07/ai-music-exceeds-50-percent-daily-uploads-deezer/) at its peak in June 2026.\n- **Video.**[Kapwing](https://www.kapwing.com/) went through the first 500 videos a brand new account gets shown and[found](https://www.kapwing.com/resources/the-tiktok-ai-slop-report/) that 59% were AI slop on TikTok and 21% on YouTube Shorts.\n- **Movies.** YouTube[shut down Screen Culture and KH Studio](https://deadline.com/2025/12/youtube-terminates-screen-culture-kh-studio-fake-ai-trailer-1236652506/) , two channels that spliced official footage with AI images into fake trailers for big franchise films, after they’d pulled in over a billion views.\n\nHardly anyone wants it though. On Deezer, all that AI music was 1 to 3% of what people actually streamed:\n\nI’m an AI engineer so I’m not against machines making things. My problem is what’s missing: nobody cared about the thing so there’s no human value in it. In my comments it comes with a disguise on top, a machine talking to me through a person who acts like it’s them. When I reply to that comment, I’m spending my time on a conversation with nobody in it.\n\n## It makes me cynical (and I won’t let it)\n\nThe worst part of slop for me is what it does to me: it makes me negative and cynical. Every polished comment now gets a little suspicion from me before it gets any warmth. I hate that.\n\nSlop doesn’t get to change me though. My humanity needs to stay constant whatever the bots do.\n\nI wrote in [What Does the Bible Say About AI?](https://tej.as/blog/what-does-the-bible-say-about-ai) that every human is made in the image of God. Nothing we build is. So the bot doesn’t get my warmth, but the person who sent it still does, like every human who writes to me in their own words, typos and all.\n\n## How to spot AI slop\n\nYou don’t need a detector for most of it, you just need to know what to look for.\n\n**The phrases.** [Claudisms](https://claudisms.ai/) is a public banlist of over 120 phrases and sentence shapes that [Claude](https://www.anthropic.com/claude) leans on: “sit with”, “load-bearing”, “the tell”, “Here’s where it gets interesting”, “the one that surprised me most”. Wikipedia’s editors keep their own field guide, [Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing), which lists the rule of three, “It’s not X, it’s Y” and words like “delve”, “tapestry” and “testament”. [Graphite](https://graphite.io/five-percent/research/ai-tells-opus-5-5-update) measured how much more often [Claude Opus 5.5](https://www.anthropic.com/claude/opus) uses some of these than people do, against human writing from before ChatGPT:\n\n116 times! People do say “this matters” (I’ve said it on stage) so one of these proves nothing on its own.\n\n**The pattern.** On LinkedIn, slop comes in a stack: a compliment about one specific detail (“especially the tokenizer test”), a number that sounds researched, “One thing I’m missing”, and a neat question to finish. Or it picks one detail and crowns it: “is the number I’d test first”, “the part that actually matters”.\n\n**The swap test.** Imagine the same comment under somebody else’s post on the same topic. Slop reads just as well there.\n\n**The shapes.** [tropes.fyi](https://tropes.fyi) keeps [a catalog of the tropes](https://tropes.fyi/tropes-md) the newest models fall into. A few of them are all over slop replies. The reply opens by handing you your own question back (ask which database to use for a side project and it starts “For a side project like yours,”). It tells you an answer exists before it gives you one (“has one big thing going for it:”). It staples an afterthought onto a sentence that was already done (“, though.” or “, beyond the basics”). And its last line points back at the one before it and crowns it (“That last part is where the two differ.”).\n\n**The vetter.** tropes.fyi also has an [AI Vetter](https://tropes.fyi/vetter): paste a link and it scores the page from “Human” to “Pure Slop”, trope by trope. I wanted to know how it decides so I fed it test pages until I could rebuild its scoring. The tropes multiply: one on a page scores about 7, 2 of them score 23 and 4 score 71. So a short comment with 2 small tells already reads as “AI-assisted”. It isn’t proof though! My post on [why I don’t like speaking at remote conferences](https://tej.as/blog/why-i-do-not-prefer-speaking-at-remote-conferences) is from 2020, years before ChatGPT. It scores 42 (“Suspicious”), mostly for starting 4 sentences in a row with “I want”. That’s just me!!\n\n## Why human writing wins\n\n**Slop costs trust.** [Oliver Schilke and Martin Reimann](https://doi.org/10.1016/j.obhdp.2025.104405) ran 13 experiments and found that people who disclosed their AI use were trusted less than people who didn’t (and being exposed by someone else cost even more). So the commenter who gets caught loses twice: once in the trust a human reply would have kept and again when somebody points it out.\n\n**The machines need us.** [Shumailov and colleagues showed in Nature](https://www.nature.com/articles/s41586-024-07566-y) that models trained on their own output lose the rare things first and drift into nonsense within a few generations. Their conclusion is that “access to the original data source must be preserved and further data not generated by LLMs must remain available.” Every human sentence on the internet is part of that original source. So slop eats the very thing the models learned from.\n\n**Only you were there.** A model can write a perfect paragraph about a tokenizer, but it wasn’t there the afternoon you ran one and can’t tell anyone what surprised you or why you cared. [Good taste](https://tej.as/blog/what-is-good-taste-in-software) stays human for the same reason: it’s judgment you build from your own experience so nobody can generate yours for you.\n\n## Is all AI slop?\n\n**No. AI output becomes slop when nobody cared enough to make the choices or check what came back.** With somebody doing both, the same tool helps make craft. Most of my talks and the design of this website are made with AI’s help these days. I use it to research, cross reference and draw connections exactly the way I would without it, just faster.\n\nI said this on stage last month, opening [The Critical Advantage With AI](https://tej.as/talks/agent-conf-2026) at [Agent Conf](https://agent.sh/) in Warsaw: “everybody now has a hammer” but “we’re not all building awesome houses”. And “we all have cameras in our phones, but you still hire a wedding photographer, or at least you maybe should, right?” I told the room there’s a very clear line between slop and craft. The rest of the talk was about taste and how the research says you build it.\n\n[Simon Willison](https://simonwillison.net/), whose [post from May 2024](https://simonwillison.net/2024/May/8/slop/) helped the word catch on, put the line in the same place: “Not all promotional content is spam, and not all AI-generated content is slop. But if it’s mindlessly generated and thrust upon someone who didn’t ask for it, slop is the perfect term for it.” He uses AI for all sorts of things and still wrote “I attach my name and stake my credibility on the things that I publish.” By the end of that year he was [describing slop](https://simonwillison.net/2024/Dec/31/llms-in-2024/) as AI content that is “both unrequested and unreviewed”.\n\n### AI slop vs. craft\n\n[Richard Sennett](https://en.wikipedia.org/wiki/Richard_Sennett) defines craftsmanship in his book [*The Craftsman*]() as “an enduring, basic human impulse, the desire to do a job well for its own sake.” He even counts Linux as craft: “technological craftsmanship, the intimate, fluid join between problem solving and problem finding.” That’s literally what building software feels like on a good day!\n\n[Ted Chiang](https://en.wikipedia.org/wiki/Ted_Chiang) makes the case against AI art in [Why A.I. Isn’t Going to Make Art](https://www.newyorker.com/culture/the-weekend-essay/why-ai-isnt-going-to-make-art). His argument is that “art is something that results from making a lot of choices.” A 100 word prompt makes about 100 of them. So a model writing a 10,000 word story from it “has to fill in for all of the choices that you are not making” (and an average of what everyone else wrote is “the least interesting choices possible”). I agree with him!! He leaves one door open, for a program nobody has built yet: one with “extremely fine-grained control” where “a person could use such a program and still deserve to be called an artist.” His one example is the film director [Bennett Miller](https://en.wikipedia.org/wiki/Bennett_Miller), who generated “more than a hundred thousand images to arrive at the twenty images in the exhibit.”\n\n### AI-assisted vs. AI-generated\n\nAmazon spells this line out for every book on [Kindle Direct Publishing (KDP)](https://kdp.amazon.com/) in its [content guidelines](https://kdp.amazon.com/en_US/help/topic/G200672390). If an AI tool created the actual text or images, the book counts as “AI-generated,” “even if you applied substantial edits afterwards.” If you “created the content yourself, and used AI-based tools to edit, refine, error-check, or otherwise improve that content”, or used one “to brainstorm and generate ideas, but ultimately created the text or images yourself”, it’s “AI-assisted”. Authors have to tell Amazon about AI-generated content. They don’t have to say anything about AI-assisted content.\n\nReaders draw the same line. For its [Generative AI and News Report 2025](https://reutersinstitute.politics.ox.ac.uk/generative-ai-and-news-report-2025-how-people-think-about-ais-role-journalism-and-society), the [Reuters Institute](https://reutersinstitute.politics.ox.ac.uk/) asked people in 6 countries (Argentina, Denmark, France, Japan, the UK and the US) how comfortable they’d be with news made in different ways:\n\nA human checking the machine’s work only raises comfort from 12% to 21%. A human leading with some AI help doubles that to 43%!! People want a person making the choices.\n\n### When AI makes your work worse\n\nIn [Fabrizio Dell’Acqua and colleagues’ experiment](https://doi.org/10.1287/orsc.2025.21838) with 758 consultants at [Boston Consulting Group (BCG)](https://www.bcg.com/), the ones using AI on 18 tasks inside what AI could do finished 12.2% more of them, 25.1% faster and with “significantly improved quality”. On a task picked to sit just outside it, they were “19% less likely to produce correct solutions” than the consultants without AI. I wrote more about this [jagged frontier](https://tej.as/blog/super-intelligence-isnt-superior) in my post on super intelligence.\n\nIt’s easy to fool yourself about it too. In a [2025 study](https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/) by [Model Evaluation and Threat Research (METR)](https://metr.org/), experienced open source developers took 19% longer with AI tools and still believed afterwards that AI had sped them up by 20%. Wild! (METR’s [2026 follow-up](https://metr.org/blog/2026-02-24-uplift-update/) estimates a speedup now, but so many developers won’t work without AI any more that METR calls its own new data “an unreliable signal”.)\n\nEven when AI helps, it pulls everyone toward the same place. [Anil Doshi and Oliver Hauser](https://doi.org/10.1126/sciadv.adn5290) gave some of 293 writers story ideas from an AI model. And those stories were rated more creative and came out more like each other. In their words, “writers are individually better off, but collectively a narrower scope of novel content is produced.” That’s the 2 LinkedIn comments from the top of this post!!\n\nAt work it has its own name now. Researchers from [BetterUp Labs](https://www.betterup.com/betterup-labs) and the [Stanford Social Media Lab](https://sml.stanford.edu/) [call it workslop in Harvard Business Review](https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity): “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” Of 1,150 full-time employees in the US, 40% had received some in the last month. Each piece took them an average of 1 hour and 56 minutes to deal with. And about half of them saw the colleague who sent it as “less creative, capable, and reliable” than before.\n\n### How I try to avoid AI slop\n\nEvery talk I give starts with me deciding what it’s about. For [The New UX](https://tej.as/talks/cityjs-london-2026) at [CityJS London](https://london.cityjsconf.org/) in April, I told Claude what I wanted to highlight (streaming interfaces instead of making people wait for a whole answer, building and using [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) servers, and [ChatGPT apps](https://developers.openai.com/apps-sdk) with their own interface) and asked it for an outline and a sample repo. The next day I was arguing with it about the demo’s API: “look man the api needs to be as lean as possible”.\n\nThen there’s research. Even [Google’s guidance on AI content](https://developers.google.com/search/docs/fundamentals/using-gen-ai-content) says “Generative AI can be particularly useful when researching a topic”. For [my post on how long a keynote should be](https://tej.as/blog/how-long-should-a-keynote-speaker-speak) I wanted to know what science sits behind the 18 minute TED talk. Following the citations back with AI got me to a paper from 1978 about note taking!! It checks me too. On stage I credit my whole definition of taste to a 1993 paper. When I checked it with AI for my post on good taste, the paper’s abstract only backed part of it. So the post says so.\n\nThis website went the same way. When I asked for a brand, I wrote down my life and then: “Red has to be a part of it for blood (mine, Christ’s, etc.). Maybe Schwarz/Rot/Gold because I love Germany too?” The AI found free typefaces close to the ones I named, measured the contrast of every color and wrote the code. It took my Schwarz/Rot/Gold and made the red line on [/story](https://tej.as/story) go missing at age 4 and come back gold. In my own notes, that gold is “because somewhere on the journey, I met God.”\n\nI throw a lot of what it makes away. “its so fugly revert it” is a whole message I sent about a redesign in July. The first version of the woven thread on /story got “the tapestry is bullshit… its just dots and lines. use vgpu”. The shader that’s on that page now came out of that message.\n\n## Sign the petition to restore humanity\n\nSigning this petition costs you nothing but a little effort:\n\n1. When you reply to a person, write it yourself (typos and all).\n2. If a machine wrote it, say so.\n3. When you see slop on LinkedIn, use the “Seems like AI slop” button in the “…” menu. It hides the post for you and helps LinkedIn learn what slop looks like.\n4. Reward the humans by replying to their posts, reposting their work and telling them when something they wrote landed.\n\nTo sign, share this post with one sentence you wrote yourself.\n\n## Questions\n\n### What is AI slop?\n\nAI slop is cheap content a machine manufactures in bulk, with no human care or value in it: songs, videos, fake movie trailers, books, posts and comments. Merriam-Webster, which made slop its 2025 word of the year, defines it as digital content of low quality that is produced usually in quantity by means of artificial intelligence. On Deezer, more than half of all new music uploaded in June 2026 was fully AI-generated. And it made up only 1 to 3% of what people actually streamed.\n\n### What are examples of AI slop?\n\nThe one I get most is a LinkedIn comment that compliments one specific detail, adds a number that sounds researched, says “One thing I'm missing” and closes on a neat question, in words that would work under anybody's post. It's everywhere: Pangram found that 41% of LinkedIn posts over 250 words were written entirely by AI. And Imperva counted 53% of all web traffic in 2025 as bots.\n\n### How do you identify AI slop?\n\nLook for the phrases models lean on and the shapes they fall into. Graphite found that Claude Opus 5.5 writes “this matters” 116 times as often as people do and “why _ matters” 92 times as often. Then try the swap test: imagine the same comment under somebody else's post on the same topic. Slop reads just as well there. The AI Vetter at tropes.fyi scores a page from \"Human\" to \"Pure Slop\", but posts written years before ChatGPT trip it too. So a bad score on its own proves nothing.\n\n### What are Claudisms?\n\nClaudisms are the phrases and sentence shapes Anthropic's Claude overuses, collected in a public banlist at claudisms.ai: “sit with”, “load-bearing”, “the tell”, “Here's where it gets interesting”, “the one that surprised me most” and over 120 more. One of them on its own proves nothing. A pile of them in one comment usually does.\n\n### Why is AI slop bad?\n\nBecause it costs trust and it poisons the well. In 13 experiments, Oliver Schilke and Martin Reimann found that people who disclosed their AI use were trusted less and that being exposed by someone else cost even more. And models trained on their own output degrade within a few generations (Shumailov and colleagues, Nature, 2024). The internet needs human writing to keep working at all.\n\n### Is all AI slop?\n\nNo. Slop is what you get when nobody cared enough to make the choices or check the machine's work. When a person does both, AI helps make craft: most of my talks and the design of my website are made with AI's help these days. Simon Willison, whose 2024 post helped the word catch on, describes slop as AI content that is both unrequested and unreviewed.\n\n### What's the difference between AI-assisted and AI-generated?\n\nAmazon's Kindle Direct Publishing (KDP) defines both. If an AI tool created the actual text or images, it's AI-generated, even if you edited it heavily afterwards. If you created the content yourself and used AI to edit, refine, error-check or brainstorm ideas, it's AI-assisted. Readers care about the difference: the Reuters Institute found 12% of people comfortable with news made entirely by AI and 43% with news a human led with some AI help.\n\n### How do you avoid making AI slop?\n\nMake the choices yourself and check what comes back. I decide what a talk argues and how my website should feel, then use AI to research, cross reference, outline and build. Then I throw out a lot of what it makes. The risk is fooling yourself: in a 2025 study by Model Evaluation and Threat Research (METR), experienced developers took 19% longer with AI tools and still believed it had sped them up by 20%.\n\nWritten by me, Tejas Kumar, an AI Engineer at IBM based in Berlin. Read [everything else I have written](https://tej.as/blog), or go to [Fluent React, my O'Reilly book on how React works inside](https://tej.as/react), [the talks I give at conferences](https://tej.as/speaking), and [ConTejas Code, my podcast](https://tej.as/podcast).\n","body_html":"

Please stop the slop. AI slop is cheap stuff a machine churns out in bulk with no human value in it: songs, videos, books, posts, and the comments under them. Last weekend it showed up under my own post. So this is my verdict on it: what it is, how to spot it, and why being human still wins. It’s also a petition you can sign at the end.

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“Does this in any way invalidate my question?”

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On 3 October I posted on LinkedIn about Kolibri, the new open German model from Aleph Alpha. The top comment opened with “Great write-up, especially the tokenizer test”, gave me a number that sounded specific, said “One thing I’m missing” and closed on a neat question. Another one opened with “The 44% vs 11% ‘I don’t know’ rate is the number I’d test first”, which read like the same assistant had written both on the same afternoon.

\n

So I asked the first one “answer honestly did you generate this reply with ai” and got another question back: “does this in any way invalidate my question or argument?”

\n

It does. So this is what I wrote back:

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So you did eh? It does invalidate your question or argument because I’m not talking to a human at this point but some machine. I prefer to keep my communication with machines to machines, not machines in disguise.

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A third person told me I was “playing AI slop card to avoid responding to legitimate questions”. My answer was “there is no ai slop card to play. I speak to humans.”

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Then I asked on X: “vibe check am i being an asshole” and most of the replies said no. Rizèl Scarlett has the same problem I do:

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No I always get AI replies on LinkedIn..that question my thoughts. And usually I tell them it sounds like they wrote it with AI.

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They can come back to me when they have a real, original thought

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October 3, 2026

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Phil Zona went straight to the point: “if it was a question asked out of true curiosity, they wouldn’t have needed AI to write those 3 sentences. they’re not actually interested in the answer.”

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Slop is most of the internet now

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I wish this were just my comment section. Pangram, a company that detects AI writing, ran over a million posts through its checker this summer and The Register reported what it found. 41% of LinkedIn posts over 250 words were written entirely by AI. On X it was 25%, with another 23.2% written with AI’s help.

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Bots now make more of the web’s traffic than people do. Imperva, which has measured bot traffic since 2013, found in its 2025 Bad Bot Report that automated traffic passed human traffic in 2024 for the first time in a decade, at 51%. In its 2026 report it was 53% (the earlier years below are from its 2022, 2023 and 2024 reports).

\n
YearBotsPeople
202142.3%57.7%
202247.4%52.6%
202349.6%50.4%
202451%49%
202553%47%
\n

LinkedIn’s chief product officer told Fortune that LinkedIn blocks “hundreds of thousands of automated slop comment attempts every day”. Every day! Whatever they’re doing, I guess they need to do it better because the slop keeps coming. In July LinkedIn added a “Seems like AI slop” button to every post and comment. Merriam-Webster even made “slop” its word of the year for 2025.

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What is AI slop?

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AI slop is cheap content a machine manufactures in bulk, with no human care or value in it. Merriam-Webster’s definition is “digital content of low quality that is produced usually in quantity by means of artificial intelligence.” Comments are the slop I see most, but it’s in everything:

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Hardly anyone wants it though. On Deezer, all that AI music was 1 to 3% of what people actually streamed:

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I’m an AI engineer so I’m not against machines making things. My problem is what’s missing: nobody cared about the thing so there’s no human value in it. In my comments it comes with a disguise on top, a machine talking to me through a person who acts like it’s them. When I reply to that comment, I’m spending my time on a conversation with nobody in it.

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It makes me cynical (and I won’t let it)

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The worst part of slop for me is what it does to me: it makes me negative and cynical. Every polished comment now gets a little suspicion from me before it gets any warmth. I hate that.

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Slop doesn’t get to change me though. My humanity needs to stay constant whatever the bots do.

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I wrote in What Does the Bible Say About AI? that every human is made in the image of God. Nothing we build is. So the bot doesn’t get my warmth, but the person who sent it still does, like every human who writes to me in their own words, typos and all.

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How to spot AI slop

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You don’t need a detector for most of it, you just need to know what to look for.

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The phrases. Claudisms is a public banlist of over 120 phrases and sentence shapes that Claude leans on: “sit with”, “load-bearing”, “the tell”, “Here’s where it gets interesting”, “the one that surprised me most”. Wikipedia’s editors keep their own field guide, Signs of AI writing, which lists the rule of three, “It’s not X, it’s Y” and words like “delve”, “tapestry” and “testament”. Graphite measured how much more often Claude Opus 5.5 uses some of these than people do, against human writing from before ChatGPT:

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116 times! People do say “this matters” (I’ve said it on stage) so one of these proves nothing on its own.

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The pattern. On LinkedIn, slop comes in a stack: a compliment about one specific detail (“especially the tokenizer test”), a number that sounds researched, “One thing I’m missing”, and a neat question to finish. Or it picks one detail and crowns it: “is the number I’d test first”, “the part that actually matters”.

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The swap test. Imagine the same comment under somebody else’s post on the same topic. Slop reads just as well there.

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The shapes. tropes.fyi keeps a catalog of the tropes the newest models fall into. A few of them are all over slop replies. The reply opens by handing you your own question back (ask which database to use for a side project and it starts “For a side project like yours,”). It tells you an answer exists before it gives you one (“has one big thing going for it:”). It staples an afterthought onto a sentence that was already done (“, though.” or “, beyond the basics”). And its last line points back at the one before it and crowns it (“That last part is where the two differ.”).

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The vetter. tropes.fyi also has an AI Vetter: paste a link and it scores the page from “Human” to “Pure Slop”, trope by trope. I wanted to know how it decides so I fed it test pages until I could rebuild its scoring. The tropes multiply: one on a page scores about 7, 2 of them score 23 and 4 score 71. So a short comment with 2 small tells already reads as “AI-assisted”. It isn’t proof though! My post on why I don’t like speaking at remote conferences is from 2020, years before ChatGPT. It scores 42 (“Suspicious”), mostly for starting 4 sentences in a row with “I want”. That’s just me!!

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Why human writing wins

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Slop costs trust. Oliver Schilke and Martin Reimann ran 13 experiments and found that people who disclosed their AI use were trusted less than people who didn’t (and being exposed by someone else cost even more). So the commenter who gets caught loses twice: once in the trust a human reply would have kept and again when somebody points it out.

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The machines need us. Shumailov and colleagues showed in Nature that models trained on their own output lose the rare things first and drift into nonsense within a few generations. Their conclusion is that “access to the original data source must be preserved and further data not generated by LLMs must remain available.” Every human sentence on the internet is part of that original source. So slop eats the very thing the models learned from.

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Only you were there. A model can write a perfect paragraph about a tokenizer, but it wasn’t there the afternoon you ran one and can’t tell anyone what surprised you or why you cared. Good taste stays human for the same reason: it’s judgment you build from your own experience so nobody can generate yours for you.

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Is all AI slop?

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No. AI output becomes slop when nobody cared enough to make the choices or check what came back. With somebody doing both, the same tool helps make craft. Most of my talks and the design of this website are made with AI’s help these days. I use it to research, cross reference and draw connections exactly the way I would without it, just faster.

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I said this on stage last month, opening The Critical Advantage With AI at Agent Conf in Warsaw: “everybody now has a hammer” but “we’re not all building awesome houses”. And “we all have cameras in our phones, but you still hire a wedding photographer, or at least you maybe should, right?” I told the room there’s a very clear line between slop and craft. The rest of the talk was about taste and how the research says you build it.

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Simon Willison, whose post from May 2024 helped the word catch on, put the line in the same place: “Not all promotional content is spam, and not all AI-generated content is slop. But if it’s mindlessly generated and thrust upon someone who didn’t ask for it, slop is the perfect term for it.” He uses AI for all sorts of things and still wrote “I attach my name and stake my credibility on the things that I publish.” By the end of that year he was describing slop as AI content that is “both unrequested and unreviewed”.

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AI slop vs. craft

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Richard Sennett defines craftsmanship in his book The Craftsman as “an enduring, basic human impulse, the desire to do a job well for its own sake.” He even counts Linux as craft: “technological craftsmanship, the intimate, fluid join between problem solving and problem finding.” That’s literally what building software feels like on a good day!

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Ted Chiang makes the case against AI art in Why A.I. Isn’t Going to Make Art. His argument is that “art is something that results from making a lot of choices.” A 100 word prompt makes about 100 of them. So a model writing a 10,000 word story from it “has to fill in for all of the choices that you are not making” (and an average of what everyone else wrote is “the least interesting choices possible”). I agree with him!! He leaves one door open, for a program nobody has built yet: one with “extremely fine-grained control” where “a person could use such a program and still deserve to be called an artist.” His one example is the film director Bennett Miller, who generated “more than a hundred thousand images to arrive at the twenty images in the exhibit.”

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AI-assisted vs. AI-generated

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Amazon spells this line out for every book on Kindle Direct Publishing (KDP) in its content guidelines. If an AI tool created the actual text or images, the book counts as “AI-generated,” “even if you applied substantial edits afterwards.” If you “created the content yourself, and used AI-based tools to edit, refine, error-check, or otherwise improve that content”, or used one “to brainstorm and generate ideas, but ultimately created the text or images yourself”, it’s “AI-assisted”. Authors have to tell Amazon about AI-generated content. They don’t have to say anything about AI-assisted content.

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Readers draw the same line. For its Generative AI and News Report 2025, the Reuters Institute asked people in 6 countries (Argentina, Denmark, France, Japan, the UK and the US) how comfortable they’d be with news made in different ways:

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A human checking the machine’s work only raises comfort from 12% to 21%. A human leading with some AI help doubles that to 43%!! People want a person making the choices.

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When AI makes your work worse

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In Fabrizio Dell’Acqua and colleagues’ experiment with 758 consultants at Boston Consulting Group (BCG), the ones using AI on 18 tasks inside what AI could do finished 12.2% more of them, 25.1% faster and with “significantly improved quality”. On a task picked to sit just outside it, they were “19% less likely to produce correct solutions” than the consultants without AI. I wrote more about this jagged frontier in my post on super intelligence.

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It’s easy to fool yourself about it too. In a 2025 study by Model Evaluation and Threat Research (METR), experienced open source developers took 19% longer with AI tools and still believed afterwards that AI had sped them up by 20%. Wild! (METR’s 2026 follow-up estimates a speedup now, but so many developers won’t work without AI any more that METR calls its own new data “an unreliable signal”.)

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Even when AI helps, it pulls everyone toward the same place. Anil Doshi and Oliver Hauser gave some of 293 writers story ideas from an AI model. And those stories were rated more creative and came out more like each other. In their words, “writers are individually better off, but collectively a narrower scope of novel content is produced.” That’s the 2 LinkedIn comments from the top of this post!!

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At work it has its own name now. Researchers from BetterUp Labs and the Stanford Social Media Lab call it workslop in Harvard Business Review: “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” Of 1,150 full-time employees in the US, 40% had received some in the last month. Each piece took them an average of 1 hour and 56 minutes to deal with. And about half of them saw the colleague who sent it as “less creative, capable, and reliable” than before.

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How I try to avoid AI slop

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Every talk I give starts with me deciding what it’s about. For The New UX at CityJS London in April, I told Claude what I wanted to highlight (streaming interfaces instead of making people wait for a whole answer, building and using Model Context Protocol (MCP) servers, and ChatGPT apps with their own interface) and asked it for an outline and a sample repo. The next day I was arguing with it about the demo’s API: “look man the api needs to be as lean as possible”.

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Then there’s research. Even Google’s guidance on AI content says “Generative AI can be particularly useful when researching a topic”. For my post on how long a keynote should be I wanted to know what science sits behind the 18 minute TED talk. Following the citations back with AI got me to a paper from 1978 about note taking!! It checks me too. On stage I credit my whole definition of taste to a 1993 paper. When I checked it with AI for my post on good taste, the paper’s abstract only backed part of it. So the post says so.

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This website went the same way. When I asked for a brand, I wrote down my life and then: “Red has to be a part of it for blood (mine, Christ’s, etc.). Maybe Schwarz/Rot/Gold because I love Germany too?” The AI found free typefaces close to the ones I named, measured the contrast of every color and wrote the code. It took my Schwarz/Rot/Gold and made the red line on /story go missing at age 4 and come back gold. In my own notes, that gold is “because somewhere on the journey, I met God.”

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I throw a lot of what it makes away. “its so fugly revert it” is a whole message I sent about a redesign in July. The first version of the woven thread on /story got “the tapestry is bullshit… its just dots and lines. use vgpu”. The shader that’s on that page now came out of that message.

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Sign the petition to restore humanity

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Signing this petition costs you nothing but a little effort:

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  1. When you reply to a person, write it yourself (typos and all).
  2. If a machine wrote it, say so.
  3. When you see slop on LinkedIn, use the “Seems like AI slop” button in the “…” menu. It hides the post for you and helps LinkedIn learn what slop looks like.
  4. Reward the humans by replying to their posts, reposting their work and telling them when something they wrote landed.
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To sign, share this post with one sentence you wrote yourself.

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Questions

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What is AI slop?

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AI slop is cheap content a machine manufactures in bulk, with no human care or value in it: songs, videos, fake movie trailers, books, posts and comments. Merriam-Webster, which made slop its 2025 word of the year, defines it as digital content of low quality that is produced usually in quantity by means of artificial intelligence. On Deezer, more than half of all new music uploaded in June 2026 was fully AI-generated. And it made up only 1 to 3% of what people actually streamed.

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What are examples of AI slop?

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The one I get most is a LinkedIn comment that compliments one specific detail, adds a number that sounds researched, says “One thing I'm missing” and closes on a neat question, in words that would work under anybody's post. It's everywhere: Pangram found that 41% of LinkedIn posts over 250 words were written entirely by AI. And Imperva counted 53% of all web traffic in 2025 as bots.

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How do you identify AI slop?

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Look for the phrases models lean on and the shapes they fall into. Graphite found that Claude Opus 5.5 writes “this matters” 116 times as often as people do and “why _ matters” 92 times as often. Then try the swap test: imagine the same comment under somebody else's post on the same topic. Slop reads just as well there. The AI Vetter at tropes.fyi scores a page from "Human" to "Pure Slop", but posts written years before ChatGPT trip it too. So a bad score on its own proves nothing.

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What are Claudisms?

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Claudisms are the phrases and sentence shapes Anthropic's Claude overuses, collected in a public banlist at claudisms.ai: “sit with”, “load-bearing”, “the tell”, “Here's where it gets interesting”, “the one that surprised me most” and over 120 more. One of them on its own proves nothing. A pile of them in one comment usually does.

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Why is AI slop bad?

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Because it costs trust and it poisons the well. In 13 experiments, Oliver Schilke and Martin Reimann found that people who disclosed their AI use were trusted less and that being exposed by someone else cost even more. And models trained on their own output degrade within a few generations (Shumailov and colleagues, Nature, 2024). The internet needs human writing to keep working at all.

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Is all AI slop?

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No. Slop is what you get when nobody cared enough to make the choices or check the machine's work. When a person does both, AI helps make craft: most of my talks and the design of my website are made with AI's help these days. Simon Willison, whose 2024 post helped the word catch on, describes slop as AI content that is both unrequested and unreviewed.

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What's the difference between AI-assisted and AI-generated?

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Amazon's Kindle Direct Publishing (KDP) defines both. If an AI tool created the actual text or images, it's AI-generated, even if you edited it heavily afterwards. If you created the content yourself and used AI to edit, refine, error-check or brainstorm ideas, it's AI-assisted. Readers care about the difference: the Reuters Institute found 12% of people comfortable with news made entirely by AI and 43% with news a human led with some AI help.

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How do you avoid making AI slop?

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Make the choices yourself and check what comes back. I decide what a talk argues and how my website should feel, then use AI to research, cross reference, outline and build. Then I throw out a lot of what it makes. The risk is fooling yourself: in a 2025 study by Model Evaluation and Threat Research (METR), experienced developers took 19% longer with AI tools and still believed it had sped them up by 20%.

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Written by me, Tejas Kumar, an AI Engineer at IBM based in Berlin. Read everything else I have written, or go to Fluent React, my O'Reilly book on how React works inside, the talks I give at conferences, and ConTejas Code, my podcast.

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