AI agents redraw internet traffic, why AI text is harder to follow, robot-arm skills doubling every 54 days, X's pointing hand, and Anduril's American-made laptop
Hello, dear TEA-mates! Here is what you need to know today.
1. 🌐 How AI Agents Could Redraw the Internet's Traffic Map
In an RCR Wireless analysis, Vish Nandlall argues AI agents will separate the traffic reaching a customer from the work done to serve them. In his illustrative flight search, a person downloads ten 2 MB pages (20 MB), while a cloud agent doing the same job moves 30.1 MB across separate connections and returns a 0.1 MB answer: 99.5% less data on the customer's connection, but 50.5% more in total. DataDome recorded agentic-browser requests to its customers jumping from 12.5 million in August 2026 to 58.2 million in September, and OpenRouter counted roughly seven times as many tokens from agent use as human use in the last week of September. Google already shifts inference requests across three US and European regions when one runs short on memory, and Lumen reports nearly $13 billion in Private Connectivity Fabric contracts, including work for Anthropic. Nandlall says network builds should be financed against identified workloads, not traffic growth alone. (Read More)
🫖 TEA For Thought: "This is definitely very, very interesting. I can definitely see it happening, especially this year. I've moved pretty much all of my local setups to the cloud, like Notion, for example, or Grokbot, which has its own computer. I've run out of space on Grokbot's computer a couple of times, so I think computers in the cloud may be a huge business, which is already the case with inference."
2. 🧠 Why AI Writing Is Getting Harder to Read
Researchers from New York University and UT Austin (Thomas Hikaru Clark, Matias B. Martin, and Kyle Mahowald) studied the widespread sense that AI text has recently become harder to understand. They built a corpus of chat, coding, and essay output from 14 models, including Claude, GPT-5.6, Kimi K2.5, and GLM 5, and measured features linked to human reading difficulty. Compared with human writing, all nine frontier and near-frontier models used more rare word pairs and more inanimate subjects with animate verbs, like "is_file() swallows that." In conversation, most also used longer dependencies, more stacked nouns, and more object relative clauses with "that" dropped. Claude Opus 5.5 scored lower than Opus 5 on 19 of 21 difficulty-linked comparisons. The authors argue that post-training for math, code, and reasoning rewards information density over communication. To test this, they trained Qwen2.5-1.5B-Instruct with a length penalty, and in some settings it chose the shorter phrasing over 98% of the time, without ever being told to. (Read More)
🫖 TEA For Thought: "This is very interesting and could be very dangerous. Imagine if, at some point, we have trouble understanding AI's output completely. It's very likely we're going to be completely controlled by AI."
3. 🦾 AI-Controlled Robot Arms Are Doubling in Skill Every 54 Days
A LessWrong post, backed by a paper submitted to TAG@CoRL, tested nine frontier multimodal models from OpenAI, Anthropic, and Google DeepMind, including GPT-6 Astra, Opus 5.5, and Gemini 4 Argon, as they directly controlled a real two-armed I2RT YAM robot. Across 15 model configurations, each ran 20 trials on each of six RoboDojo tasks, such as stacking bowls, capping a pen, and putting objects in a safe. On this benchmark, the fitted trend from July to October 2026 implies performance doubling every 53.9 days (95% interval: 36.1 to 59.5 days). The best execution rate rose 4.4x, from 12.4 to 54.4 subtasks per hour, while the lowest cost fell 6.2x, from $2.36 to $0.38 per subtask. Top models still averaged only 45% to 48% task scores, held back mostly by efficiency: they rarely got stuck, but missed grasps and fumbled objects. RoboDojo records human teleoperators at 25 to 40 seconds per task, and the author's naive extrapolation has models catching up by mid-2027. (Read More)
🫖 TEA For Thought: "If current speed and accuracy trends continue at this pace, AI-controlled robot arms could reach the speed and precision of human teleoperators by mid-2027… Then what's next? It's hard to picture what the future looks like, even a month from now…"
4. 👉 X Is Pointing a Giant Hand at Its Promote Button
A growing number of X users reported that a hand pointing at the "promote" button, which lets users pay to boost a post, suddenly appeared while they were writing, TechCrunch reported on October 26. The nudge irked users across the board. With Halloween days away, TechCrunch noted it could be a prank, though X has not said so, and that the hand might scare off even users who wanted to pay for promotion. TBPN podcast president Dylan Abruscato called it the "most Nikita-coded thing I've ever seen," a nod to growth tactics tied to Nikita Bier, who left as X's head of product in August after almost a year. On Monday, Peter Sellis, Bier's former boss and ex-head of product at Snap and Discord, posted that he has taken over as X's product chief. It is unclear whether the hand is his doing, and TechCrunch has asked X for comment. (Read More)
🫖 TEA For Thought: "I also got the big hand. Very absurd, but definitely good marketing during Halloween week."
5. 💻 Anduril and Qualcomm Want to Build an American-Made Laptop
Anduril and Qualcomm are partnering on BlueChip, a laptop line launching in early 2027. The first prototype is a ruggedized military model with Arm-based Snapdragon X series chips, a rifle-strap-style carrying handle, and a choice of Windows or two undisclosed Linux versions. It will be "designed and assembled in the United States" at Anduril's Arsenal-1 facility in Ohio, and Qualcomm CEO Cristiano Amon said Qualcomm intends to make the processors at TSMC Arizona. Anduril founder Palmer Luckey said the share of US-made components is "TBD," naming only the display glass, the display frame, and parts of the ribbon component as American-made from the start, and said the first laptop most likely won't be 100% American. The Verge notes that would likely fall below the 65% threshold for American-made under federal procurement rules. Luckey said the project is funded by the two companies, not government subsidies, with first responders and eventually consumers to follow the military. (Read More)
🫖 TEA For Thought: "This is a good start. The U.S. has to start building everything from scratch for itself. Hardware is hard, but it's life or death."
🛠️ Skill of the Day
The Plain-Talk Contract: Sets house rules so an AI's answers read like a clear explanation from a person, not a dense wall of compressed jargon.
For the rest of this conversation, write for a busy human reader, not for another AI. Follow these rules in every answer:
1. Lead with the answer in one or two sentences, then give the details.
2. Keep each subject close to its verb. If a sentence needs a second clause, split it into two sentences.
3. Use plain, literal verbs. Write "this step takes a long time," not "this step eats your afternoon."
4. Never stack three or more nouns in a row (no "customer onboarding flow redesign"). Unpack them with "of," "for," or a short phrase.
5. Keep small words like "that" and "which" when they make a sentence easier to follow.
6. Use common words. If you need a technical term, define it in plain words the first time.
Before you send each answer, reread it as someone new to the topic and rewrite any sentence you had to read twice.
My first question: [YOUR QUESTION HERE]Paste it at the start of a new chat in ChatGPT, Claude, or your tool of choice, then replace the bracketed bit with your question.
TEAHEE Moment
Stay sharp, stay informed. See you tomorrow.
If you enjoyed this TEA, follow along on social for more: