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お前たちをパンツにしてやる！ I'm going to turn you all into underwear! 我要把你們變成內褲！ #靈異教師神眉# #眠鬼# #地獄先生ぬ〜べ〜# #HellTeacherNube# #Menki#

X AI ALGORITHM UPDATE (BIG ONE) 🚨 X updated their open source algorithm yesterday and the biggest number in it is gone: copy link went from 20 to 0 points. Small accounts should focus on: posts people like, reply to and stay on (so stop counting on link copies) tl;dr: - on Nov 13 X's open source code set the score for copying a post's link to 0 - copy link: 20 → 0 - it was the top score in the whole system, 4x a reply - the code also names a "copy link bait" spam check - likes (0.708), replies (5) and DM shares (5) didn't move full details: - The number that's gone Since I started reading X's open source code in August, one number sat at the top: 20, for someone tapping share and copying your post's link. Nothing else came close. As of the Nov 13 release, it's 0. X still guesses who'll copy your link. It just multiplies that guess by 0 now. X didn't explain it. It's just what the code says. (I check the open source algo daily with Claude and share updates with you) - Cross it off your list My own checklist called copy link the biggest number. Last week's post said it too. It was true then. It isn't now. If you saved that list, cross that line out. - The "copy link bait" check X's code now mentions a spam check called "copy link bait". In the code it adds a spam label to the post, and that label already keeps a post out of strangers' feeds. It only shows up in a test, so I can't see if it's running or how strict it is. My read: X saw people baiting link copies, so it turned the score off and built something to catch the bait. That's a read, the code doesn't say why. - Why that matters if you're small If your plan was posts people copy the link to, that plan now earns 0 in X's ranking. A copied link can still bring people in from outside X. It just doesn't push your post up anymore. What still pays: likes at 0.708 (the highest ever), people staying on your post, replies at 5 and back and forth with mutuals at 20. - Also new: photo and video tags If a post has a spam label, people you tag in its photo or video who don't follow you won't get notified. Same idea as last week's rule for replies. - What didn't change Every other score. Your new posts still get their extra push in the first 2 hours and first 200 views, and early likes still pick which one gets it. Here's a recap of what you should be doing: - aim for likes, replies and time spent, the copy link score is gone - a DM share still earns 5, same as a reply or a quote - likes sit at 0.708, never higher - time on your post keeps counting at its best rate yet - 10+ seconds after someone taps in adds 0.385 - write your replies yourself, under big accounts most of all - give people a reason to hang around your profile - in videos the opening seconds carry it, an open alone scores 0 - posts read to the end help X find you strangers - smaller accounts (below 50K) get a shot at a spot near 16 for a fresh original - early likes decide which new post gets that spot - post when your followers are awake, the push lasts 2 hours and 200 views - mutuals going back and forth earn 20, so follow back the regulars - only your originals ever get shown to strangers - like 1 and like 32 each unlock another way to reach strangers - one strong post per feed, your second only counts 62% - clips longer than 10 seconds for the video lists - a post likely to win you a follow gets +4 - give your pinned post a look, it can affect the whole account What you should NOT be doing: - counting on copy link shares, they score 0 now - baiting link copies, the code names a spam check for exactly that - a spam label also stops your photo tags reaching non-followers - AI-written replies under big accounts, "llm slop" is a flag X uses - copy-paste replies, labeled ones skip non-followers' notifications - chasing taps, 0.274 and dropping - drifting off your topic, each probable "not interested" takes 53.07 away - videos people open and leave, the open itself earns 0 - posting at 3am, it wastes the 2 hour push - expecting replies and reposts to reach strangers - an insult label, it hides that post from non-followers - earning a misinfo or low quality label, which adds a warning and locks strangers out of liking or sharing - 3 adult photos or videos among your latest 5 posts, that puts a label on you - forgetting videos get rechecked at 64 and 512 likes - one account label and strangers stop seeing you - pinning a link to a site X rates badly, that can mean a label for a week - posting your own old words again risks the copypasta flag - a low quality link plus tagged strangers reads as spam - bait for engagement, big or small it gets a label - several posts back to back, they split the same feed - hashtag piles, they do nothing - bookmarks for reach, they score 0 - hoping a 3 day old post still lands in For You, it stops at 2 days

An American porn actress says a single shoot in Madrid involved 80 men and nearly a liter of semen. She counted 122 ejaculations, followed by another 10 onto her face. The night before, she had sat across from the director asking about pay and medical testing. He answered by opening a spreadsheet. In the interview below, she describes how the production was organized, from recruiting performers to deciding when she could take a break. According to her, the studio maintained a roster of around 300 men in Madrid. Getting onto it required a referral. Test results fed into the spreadsheet so the crew could track who was cleared to participate. The men could earn more depending on the shot they delivered. She says she was given three medications before filming, including one she describes as a muscle relaxant. Nine women worked as fluffers. Their waiting room had pink furniture and candy on the table. Outside, the men lined up while her videos played on a television. The shoot followed a repeating schedule: ten ejaculations into her mouth, swallow, then another ten. After fifty, she took a break and recorded an interview before returning. One assistant held a bowl beneath her chin to catch whatever spilled. She says the role even had a name: “scooper.” Amid all that coordination, she remembers one man missing and quietly apologizing. “I’m so sorry. I’m so sorry.” For the final sequence, she requested ten men instead of the usual five. Then the director addressed the group in Spanish. One word caught her attention: “ojos.” Eyes. Afterward, she asked whether he had instructed them to aim at her eyes. He denied it. According to her, he had repeated something she mentioned over dinner - that she didn’t mind and the men interpreted it differently. She has since referred other American performers to the production. “I’ve sent them so many Americans.”

if you want to automerge thousands of pull requests , this is how she does it (via @poteto). 809 in june. 10,926 in october. merged prs a month that touch the grok bot team's code. i went through her posts and put the setup in one place. every pr still gets an agentic risk review plus bugbot. low- and medium-risk ones automerge. only higher-risk ones get a person. day to day, in her words, it's just grok bot and cursor projects. she used to have more cursor automations and replaced them with slack bots that have routines. she works on many streams in parallel with pstack: perf, bug fixes, agent-friendly refactors, her own skills, features, ui polish, the harness, release and observability. not from sitting in a review inbox. she's said the speed gains come from parallelizing. a single chat can take longer because of verification. she handholds it less, so she can run several large projects at once. the real setup is in the codebase and the checks around it. she treats the codebase as memory. every agent mistake needs to turn into a constraint. her team built their own framework for grok bot so some anti-patterns become hard to write at all. agents have to verify their own work. they run the app, and can sometimes model it in tla+. they produce screenshots or video that are easier to check than the whole pr. formal verification skills and ordinary run-and-debug skills work together. she calls this an inverse pyramid. push as much as you can into determinism (fuzzing, property tests, formal and runtime verification, stricter languages) instead of spinning up more agent swarms. in her oct 6 post, she tells sandcastle, a grok team bot, to cut. it runs a buildkite dry run, dms every pr author (they can object), kicks the build, and watches it. then it starts a fuzz swarm: usually 10+ agents on grok 4.7 xhigh, some directed, some chaos monkey, using their verification skills and feature map. when something is high priority, she tells sandcastle to @ mention poteto, her engineer bot, which then spins up a cursor project to triage and fix. her team ships a new stable version of the client at least once a day. that's a lot of machinery under "just grok bot and cursor projects."

Huge AI announcements from OpenAI, Anthropic, Meta, and Google in the past 48 hours. Here's everything going on in AI right now: 1. The authors of AI 2027 just moved their timelines up. They now expect AI on par with the best human AI researchers to arrive in 2027, after METR estimated Anthropic is improving about 2x as fast thanks to AI. Daniel Kokotajlo gives it a 50-50 chance by May 2027 and says he's "scared, sad, and angry." 2. Anthropic opened the investor pitch for its IPO, with shares likely trading as soon as Thursday next week. An updated filing also says it has now crossed its own safety line for AI-driven progress. 3. OpenAI launched Businesses in ChatGPT, a beta hub where brands can set up AI agents for shoppers, claim a verified profile, and track how often ChatGPT mentions them. Paid ads can point users to those agents too. This is like the start of SEO for chatbots. 4. Anthropic rolled out Claude Sheets and Whiteboards in beta, made Claude Data generally available, and announced Claude Meetings, an assistant that sits in on your video calls. Add those to Slides, Design, and Docs. Seems like Claude is slowly rebuilding the entire office suite. 5. Anthropic also released Claude Fable 5.2 and Mythos 5.2 yesterday, with Fable debuting at #1# on Artificial Analysis' Intelligence Index, 5 points ahead of Google's Gemini 4 Carbon. It's also 20% cheaper and up to 30% faster than 5.1. Google lost the top spot before Carbon even shipped (!) 6. Meta released Muse Ember, its smallest model, built for high-volume agent work. It ties Claude Haiku 5.5 on the Intelligence Index at roughly one-third of the cost per task ($0.14 vs. $0.41 on an average test). Meta shipped its first Muse model in April and now has an answer for every tier OpenAI and Anthropic sell. 7. Google announced 2 new AI chips coming next year: the TPU 8tx, which keeps data encrypted even while a model is working on it, and the 8i Max, which joins 2 chips into one for agents that need to hold an entire codebase in view. Google already has nearly 100 TPU customers (including Anthropic and Apple) and every available chip is spoken for. 8. Nvidia's top lawyer reportedly emailed agents in August 2025 while they were investigating whether Singapore's Megaspeed smuggled its chips to China. The Commerce Department then halted the case and handed it to the Justice Department. Not a great week for Nvidia. 9. Adobe signed a multi-year deal with Disney to build custom AI models trained on Disney's characters and visual styles, with work already underway for theme parks, film, and ESPN. Pretty interesting to see one of the most protective IP owners in entertainment is now training its own AI models. 10. OpenAI acquired Odessia, a months-old AI trip-planning startup from Sonder founder Francis Davidson, who is joining OpenAI to work on travel. Between this and #3#, ChatGPT is coming for shopping and travel. 11. France unveiled the Paris Call for AI Safety and Security, with OpenAI, Anthropic, and Mistral committing to build emergency off switches into their most advanced models. Interesting timing given #1# on this list. Daily reminder that this is the worst AI will ever be.

for the first time ever, I'm sharing everything I do across all my SaaS to rank on Google and get mentioned by AI every SEO and AEO lesson I've learned is here: 1. we show up in Reddit threads. AI pulls a lot of its answers from Reddit, so Bazzly finds the threads that are fresh, and even the ones already ranking on Google, and gets our products into the top reply 2. we get our products listed #1# in listicles that already rank on Google, with Outrank. when someone asks ChatGPT for the best tool, those are the pages it reads 3. we turn Reddit questions into blog articles. Bazzly shows us what people actually ask, and we feed those questions to Outrank 4. I regularly sit down and find new niches where our products could be useful. I research each one and feed it to Outrank, and Outrank finds new ones on its own too, so our keyword plans keep expanding into new markets 5. we publish an SEO article on our own blogs every day, also with Outrank 6. Outrank helps us refresh old articles regularly. AI and Google both prefer recent pages, so every page has to stay current 7. we build new backlinks every week with Outrank, and every placement gets verified. we also pitch guest posts using Outrank's free guest post database of 278 checked sites, all DR 20+ 8. we regularly ship extremely useful free tools for potential users, and each one ranks on Google and brings people into our products 9. every month we check which AI answers name our products and which don't Outrank's AI Visibility Checker asks ChatGPT, Claude, Gemini and Perplexity real buyer questions, then shows whether we got named, which competitors did, and which sources got cited we feed those sources back into Bazzly, Outrank and our internal social content all of this brings in new users, and then we run loops that turn them into champions who spread the word 10. we incentivize our users to share honest reviews of our products on Instagram, TikTok, X and LinkedIn, and on public review sites 11. we let our users become affiliates, and then we help them make better content about our products. in the last 30 days, ~$8K has been generated by Revid affiliates alone basically every SEO and AEO lesson I learn building Outrank and Bazzly goes straight into every product I run and the idea behind all of it is simple AI recommends the most mentioned product so we make sure every one of our products gets mentioned everywhere Google and AI look: all sorts of blogs, listicles, Reddit, review sites and social and this setup does the job extremely well, for every product we run

I just jumped on the @paperdao_xyz whitelist and wanted to share how simple it was to apply. First, I made a post about Paperdao, then headed over to @daosdotworld found PaperDao, filled out the application, linked my X account, and pasted the post I created. Done in minutes. Why am I so into this project? Perpetual trading is gaining massive traction right now, and it’s shaping up to be one of the biggest trends this cycle. Even the U.S. president mentioned hyperliquid, with that guy smirking behind him proof it’s hot. As perps make their way into the U.S. market, expect a huge spike in trading volume and activity. That’s a major draw. What really pulls me toward Paper Trade is their clever setup: when you close a losing trade or get liquidated, the full loss goes to the liquidity providers, but the protocol mints $/PAPER tokens to you. This means $PAPER is only created through this mechanism, giving traders some value back even when they lose. It’s a better experience for newer traders aiming to find their footing. Losses help keep winners, losers, and stakers all rewarded a small win for everyone involved. That’s why I’m all in on this.