I started to see articles about mycorrhizal fungi pop up on sites and LLMs. In January of 2026 an evolutionary biologist won a prize regarding the fungi, there were some interviews and media items surrounding it. But then I could trace the original media items to AI content aggregators, which led to other AI generated posts about mycorrhizal fungi, and some of that entered LLM training data, causing LLMs to bring up the topic.
And here I am, a human, writing about it, which may get consumed into training pipelines and help disseminate the idea into the future even further.
In the last few years I have been going back to RSS feeds, subscribing to blogs I like. What I lose there is that I don't get suggestions for blogs I don't already know.
I genuinely wonder if there could be an opportunity for webrings there. Like blogs could have an RSS feed of "blogs I follow" by the author, and I could choose to follow them or at least visit them and selectively subscribe.
The thing is that many times, there is one article I like in a blog but not necessarily the rest. So more than "blogs I follow", it could be "articles I liked". So that if I subscribe to the RSS feed of someone, I get exposed to articles they "bookmarked", and eventually it can help me discover blogs I want to subscribe to.
Or maybe it all exists already. Or used to exist, probably.
On Instagram, I'll get fed "real" content, but you read the description and it's this giant 3-4 paragraph thing that I don't bother to read because I know with certainty that it's AI slop. Before AI, the descriptions of sports videos or meme videos were 2 sentences, now they're entire theses.
The only people left reading this crap are people that still haven't caught up with the concept of AI slop
[1] https://hai.stanford.edu/news/ai-detectors-biased-against-no...
We've societally come to the consensus that, we want to reward a race to the bottom slop. passive scrollers by not doing anything about it, active posters by contributing to it.
but there is no way else to win in this game.
A friend of mine writes the most human curated thoughtful newsletter about AI, spending 100 hours. and maybe 200 people know of its existence.
1) Glorified Rolodex
2) Place too see which of my peers got promoted or moved dormant
3) Source material for /r/linkedinlunatics
Reading the crap in the feed has never been a thing
Without naming names I saw one post where a certain team was taken to a high altitude location to lock down together and the founder was proud of people using oxygen and still getting work done.
Are we working for AI or is AI working for us?
- If you're a job seeker, most of the jobs are fake for pretend growth optics. - If you're a senior level or executive you're targeted non-stop by sales people telling you about "the conversations they're having ..." - If you're looking for actual thought leadership or interesting information, you're bombarded with random tik-tok style videos, totally contrived stories and "lessons" to how ordering at Starbucks is like managing cloud infrastructure
It's turned into a completely artificial and useless community because Microsoft chased the same growth and engagement metrics as Facebook did, now no one considers it to be a place for serious discussion.
Pangram tries to look for common patterns (rule of three, em dashes, etc.) but these are heuristic methods and not to be taken as gospel. There is no provable method to make a distinction between AI and human-generated other than the fact that AI-generated text tends to reek of pseudo-intellectual undergrad with a thesaurus.
What I don't get is how these people don't feel shame in their super obvious blatant use of LLMs for everything, even responding to posts. Maybe it's just me but when I'm attaching things to my name like that, I would absolutely not want everything to be obviously slop shit. Do they think people can't tell or something? I know at least every technical person I know can immediately tell (most of the time) when writing is LLM generated.
If I see a post that starts with this type of sentence structure I don't even bother to read any of it. I feelt like this happens on LinkedIn the most, so I'm happy to finally have some data to back up my observations.
That aside I used to scroll it fairly often to see updates or relevant posts. But itβs some combination of algorithm and LLMs, the feed is now useless, itβs all just people I donβt know posting slope about someone βjust said the quiet part out loudβ or whatever, with the obligatory GPT slop photo. Itβs unrecognizable vs a few years ago.
Maybe, but it continues to be one of the best places to find work.
The problem is when I can eventually tell the difference.
I did the same but I'm aware that LinkedIn is probably how people got in touch with me in the past, eventually leading to a job. So I'm waiting before not having looked back until the next time I need a job :) Regardless, it's not the world I want to live in anymore so you just gotta disconnect.
I used to have decent luck with Who is hiring threads but not recently as there's relatively little for mid level engineers.
It's bleak out there, on the internet.
We should get back to having our own experiences regardless of what the consensus says. If it looks good _to you_, it might just be good _for you_.
It's not exactly the same thing, of course, but still interesting the extent to which this type of content is viewed as the business opportunity for him.
Now we have these tech-savvy people generating worthless images and producing generic, emoji-infested takeaways.
> rule of three, em dashes, etc
You appear to be misinformed about how Pangram specifically works, it is not based on pattern detection of that sort. I recommend reading their whitepaper, it's a pretty understandable explanation of exactly how they trained their classifier.
It's trivial to see how many people think Pangram is absolute trash[1] (because it is).
> You appear to be misinformed about how Pangram specifically works, it is not based on pattern detection of that sort. I recommend reading their whitepaper, it's a pretty understandable explanation of exactly how they trained their classifier.
I did read their paper (which is, by the way, very scant on details), and they trained their classifier in the laziest way possible: here's a chunk of "human-written" text and here's a chunk of "AI-written" text, put them in the right bucket, and do this a zillion times. Literally zero sophistication. Also: what do you think "pattern recognition" is, if not a "classifier"?
[1] https://www.reddit.com/r/academia/comments/1rm11rs/pangram_c...
Two months ago, we launched our Chrome extension to help combat the rising slop problem on social media. It lets users scan posts on social media as they scroll, flagging AI-generated content so they can make informed decisions about how they spend their attention.
Pangram is a research-first company, not just for our industry-leading AI detection algorithms, but for tracking the risk and prevalence of AI-generated content. Social media is one of the hardest domains to study here β much harder than, say, news articles, research papers, or Amazon reviews. But it's also one of the most crucial, because it's potentially the highest-volume source of AI-generated content we face.
We believe it's important to understand this problem so that we can better combat it. That's why we included an opt-in setting in our Chrome extension, to allow users to aid our research by anonymously sharing their scan statistics with us. We've compiled the first few months of this data into the report below.
AI-generated content appeared across all social media platforms in our data set. The average AI rate across all scanned items was 13.8%, but specific rates varied by platform and item length. On four out of five platforms, longer content was more likely to be AI-generated than shortform content. Across all platforms, one in four longform items (25.72% of items over 250 words) were fully AI-generated.

Substack was an exception; there, the rate of fully AI-generated content remained fairly flat, and longer, more substantial posts were actually slightly less likely to be AI-generated compared to shorter ones.
LinkedIn was the most AI-saturated platform, where more than 40% of longform posts flagged as fully AI-generated. However, if we included mixed AI and human content, X/Twitter was the worst off: almost half of X articles were either fully AI-generated (23.9%) or AI-assisted/mixed (22.9%), with only 53.2% of X articles flagging as fully human-authored.

Our data shows that AI-generated content is a problem across all platforms, and it is hitting longform content especially hard. Even Substack, which was the longform platform with the lowest combined AI rate, still saw more than a fifth of its posts (21.9%) flag as AI-generated or AI-assisted. This is consistent with the rise of AI-generated content we're seeing in writing elsewhere, such as in newspaper opinion pieces.
LinkedIn had the highest AI share of any platform across the board. LinkedIn posts made up a third of scanned items, yet it accounted for nearly two-thirds (62%) of all AI content we flagged. Contrary to what one might expect, people are overwhelmingly willing to use AI to speak on their behalf in professional settings that are associated with their real identity, and less likely to use it on casual and anonymous platforms.

LinkedIn also encourages AI use on its platform in several ways, including a built-in "Write with AI" button (now rebranded "Enhance post," but still offering AI writing assistance). People are noticing LinkedIn's growing reputation for slop β perhaps to combat it, an executive at LinkedIn recently announced that the platform would be detecting and downranking AI-generated posts using an in-house algorithm; ironically, the announcement was itself AI-generated. Whether or not the company is attempting to modulate AI in their feed, our users are still seeing a lot of AI writing on LinkedIn.
In our data, Reddit had the highest scan volume of any platform, making up 36.7% of items that we scanned. Yet at just 4.4%, Reddit had one of the lowest combined AI shares of any platform. This is due to a composition effect: replies on Reddit were overwhelmingly human-authored (98.1%) and replies altogether made up 72% of Reddit items that we scanned. Top-level posts on Reddit were much more likely to be AI-written, at 11.6% of posts, in line with X/Twitter's 10.0% AI-saturation. The same pattern held on LinkedIn, albeit to a lesser extent: a top-level LinkedIn post was 1.35x more likely to be AI-generated than a comment.

Although LinkedIn replies were less likely to be AI-generated than posts, the effect reverses when controlling for length: LinkedIn comments were actually slightly more likely to be AI compared to top-level posts. For Reddit, the difference in AI rate was independent of post format β when controlling for length, top-level Reddit posts still had a 5.25x greater chance of being AI-generated.
Reddit's AI-free replies point to a blind spot of many anti-botting strategies. While Reddit's spam policy effectively eliminates accounts that use AI to automatically generate spam replies, this approach only catches the lowest-effort spam content on the platform. Top-level Reddit posts only make up a quarter of all Reddit items, but they have far more audience impact, and their lower volume allows AI-authored posts to slip past volume-based moderation like rate-limiting.
Collectively, since the Chrome Extension's launch on April 24th 2026, users who opted into sharing their data for research helped us create a dataset of 1,002,627 posts across several of the largest social media platforms on the internet: LinkedIn, Medium, Substack, X/Twitter, and Reddit. Each post in our dataset is counted only once, and we only scan items that are longer than 50 words. Every post was analyzed with Pangram 3.3, our latest AI detection model, which achieves a 0.01% false positive rate. This dataset allows us a direct window into what AI-generated content people are seeing on their feeds at this point in time.
AI writing is now a problem everywhere on social media. This is concerning, but it's in line with what we're seeing elsewhere online: researchers estimated that 35% of newly published websites on the open internet were AI-generated or AI-assisted. An internet that is completely flooded with undisclosed AI content is bleak, but we don't believe it's inevitable. We hope that by providing transparency to AI-generated content online, we can give internet users back some control of how they spend their attention.