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It gets better every minute.🥵😋#bigass #bigbooty #cum #thickthighs #tattoo #girlswithtattoos #riding #ridingdildo #heels #highheels #Culona

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I just press a button… and my Tesla takes me to my destination. No stress, no constant steering, no thinking about every little turn. It just drives me safely there. And honestly, it’s hard to explain this feeling to someone who hasn’t experienced the latest software yet. It’s freakin 2026... If your car isn’t electric and can’t take you from parking lot to parking lot by itself, it's like using a flip phone with a keyboard… or riding a horse in this era. That might sound dramatic, but once you see what’s actually happening behind the scenes, it starts to make sense. When I activate Tesla’s Full Self-Driving, the car is doing far more than simple cruise control that other car companies show off... it's really funny when I see them advertise it tbh. My Tesla is literally watching the world around it with eight cameras that give it a full 360° view. All that video feeds into the onboard AI computer inside the car, which is constantly analyzing everything around it like cars, lanes, pedestrians, traffic lights, construction zones, and making decisions in real time. Tesla has millions of cars on the road, and every single one is helping train the system. Even when people are driving manually, the AI is running quietly in the background predicting what it would do in that situation. And when something unusual happens, a weird intersection, a sudden obstacle, an unexpected move from another driver, that short clip gets sent back to Tesla’s data systems. Engineers then use those clips to train the next version of the driving AI. And that updated AI then gets pushed back to every Tesla through a software update. So literally overnight, your car wakes up smarter. This is what we call the Tesla’s AI flywheel. The more cars on the road, the more data the system learns from. The more it learns, the better the driving gets. The better the driving gets, the more people use it. And that cycle just keeps spinning faster. At this point the fleet has driven billions of miles using FSD, which means the system has already experienced situations that no single human driver could ever see in a lifetime. That’s why when you press that button, the car is running a massive neural network that learned from millions of real drivers and billions of miles on real roads. And the result is something that honestly feels like the future. You literally just press a button… then you arrive at your destination. I really don't know how anyone in their right mind would choose anything other than a Tesla.

Teslaconomics

19,059 views • 6 months ago

A meta-analysis of 3,075 college students just settled the laptop vs paper debate. Handwriting won. The effect size: r = -0.142 favoring pen. Translated to actual outcomes, switching from pen to laptop pushes 25% of students from above the mean to below it. In education research, that's a massive intervention. The mechanism is the boring part everyone misses. Lecture speech runs around 125 words per minute. Handwriting tops out around 22 wpm. Touch-typing hits 40-60 wpm. Do the math. The laptop user has enough bandwidth to transcribe what the professor said. The pen user does not. So the pen user has to summarize in real time. They strip filler, group ideas, reword the concept in their own language, decide what to skip. Every second of writing is an act of synthesis. The laptop user is running OCR. The pen user is running compression. This is why the laptop user with better notes scores worse on the test. Their notes contain more information. Their brain processed less of it. The notes won. The student lost. The friction was the feature. Now extend the principle. LLMs autocomplete code. Grammarly rewrites sentences. ChatGPT drafts emails. Each removes the bandwidth bottleneck the way a laptop removes it from notetaking. The output gets better. The encoding gets worse. The students who outsource their writing to AI today are running the same experiment, with the same result, ten years later in their careers. Pen and paper is the last interface slow enough to make you think.

Aakash Gupta

21,936 views • 4 months ago

In the 2025 playoffs, Shai Gilgeous Alexander attempted the MOST free-throws by a player (217) in the last 14 years. There were tons of viral videos during that run of flops and phantom foul calls that ultimately made fans everywhere question the legitimacy of their eventual NBA title. Other videos also went viral of OKC players like Lu Dort not being whistled for mauling their opponents. Basketball fans noted the hypocrisy. That also carried into this season too, where NBA coaches like Chris Finch, Nick Nurse, Mike Brown, and JB Bickerstaff made public comments about OKC’s favorable whistle. In many arena’s fans let Shai and OKC know about it as the “free-throw merchant” chants echoed in the building many times when Shai went to the line. The issue many have noted isn’t the number of free-throws that Shai gets, or the number of attempts disparity between OKC and their opponents, but it has always been about the type of fouls that are called. It seems that OKC’s strategy going into games has been to foul multiple times every possession, using the “they can’t call them all” approach. The problem with that strategy is that every team hasn’t been afforded that same luxury. If OKC fouls on every possession of a 48 minute game, and their opponent only does it 25% of their possessions, but OKC takes 5 less free-throws, did the opponent really get a better whistle?? Now the world is watching as the 2026 NBA playoffs begin. Will basketball fans finally see a level playing field for all 16 teams?? Only time will tell.

HeroOfTheDay

21,158 views • 5 months ago

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

GREG ISENBERG

377,138 views • 6 months ago

BREAKING: Anthropic just dropped Claude Fable 5—this is Mythos, made safe for public release. It is the best coding model in the world. We've been testing it internally Every 📧 for the last week or so across coding, writing, marketing, editing, and more—here's our vibe check: - It broke our benchmarks. Fable scored a 91/100 on our Senior Engineer benchmark—this is human senior engineer level. The previous high score was Opus 4.8 at 63. GPT-5.5 is a 62. - It's a one-shot wonder. You can set it and forget for hours or overnight on huge coding tasks, and come back to completed work. It cleared entire production bug backlogs, built a playable 3D, and even made a 2-minute animated film—all one-shot. - Taste and attention to detail. In coding and knowledge work tasks, it has much better taste and attention to detail than we've ever seen. It gets subtle things right, adds little features you might not have thought of, and generally understands the assignment in ways that surprised us. - Great use of context. We set it loose analyzing customer feedback surveys and our website data and it came back with a crisp, clean report that identified a. our biggest problem and b. a concrete testable solution—and then we sent it off to build that. - It's best for power users. If you're already used to orchestrating multiple agents in your work, this model can do things that you've never seen before. If you're a knowledge worker or vibe coder with a more basic setup, you're not going to notice a huge difference—in fact, it probably isn't the right model for you. - It's very slow, token-hungry. Using this thing for regular knowledge work is like squashing an ant with a rocket launcher. It also routinely uses 500k to 1M tokens on tasks. That's why it's best for your heaviest jobs—but not as good for tasks like collaborative writing. - It's expensive. It's about twice as expensive as Opus, and it's also incredibly token hungry—so expect it to be something you'll use sparingly unless your company pays for it. Overall, I think of it like a warp drive for coding: It can get you across the galaxy in a few hours, when it used to take months or years. But it's not appropriate for getting around town—you need something faster, cheaper, and more maneuverable. The ceiling is extraordinarily high on this model though. Even our most advanced testers like Kieran Klaassen felt like they were only scratching the surface of it. Want our full vibe check with all of our testing and benchmarks? Read it on Every 📧:

Dan Shipper

621,978 views • 3 months ago

Andrew Wilkinson (Andrew Wilkinson) has been waking up at 4 a.m. because he can’t stop building with Anthropic’s Opus 4.5. He started vibe coding a couple of years ago, but it felt like the Palm Treo era of the smartphone—exciting, but not quite there. You could generate an app, but it would get stuck in bug loops or break the moment you pushed it further. Then he tried Opus 4.5 in Claude Code. It felt, he says, like having a “$100,000-a-month payroll of engineers” working for him 24/7. He’s built practical AI automations into every corner of his work and life, including: - A relationship counselor app called Deep Personality that consolidates 20 clinically validated personality tests into a 40-minute assessment, then generates a 45-page analysis. When both partners complete it, it maps compatibility and predicts conflicts—Wilkinson says it laid out every fight he and his girlfriend have. - A custom email client he built by handing Claude Code his Gmail credentials and describing his ideal workflow. It triages emails by priority and sender, handles quick replies via multiple choice, and walks him through complex emails question by question before drafting. - A personal stylist that texts him four outfit recommendations every morning. It checks the weather, pulls from a spreadsheet of his entire wardrobe (photos converted to CSV by Claude), generates four outfit options rendered as images with Nano Banana 2, and texts him what to wear down to the watch. - A Lindy agent that acts as an AI referee of sorts—it records his meetings and texts him if it detects psychological red flags like manipulation or gaslighting. The bar is high—he only gets a notification every few months—but when he does, it usually confirms a gut feeling he already had. Andrew is the cofounder of Tiny, the holding company that owns businesses like AeroPress and Dribbble. Earlier in his career, Andrew was a web designer, and he fits one of my predictions for 2026: Designers, who know how to create great experiences for users, are the unsung group most empowered by this AI moment. I had him on Every 📧's AI & I to talk about Opus 4.5, what he’s building with it, and how it’s changing the way he thinks about acquiring software businesses at Tiny. This is a must-watch for anyone who wants to put AI to work in their day-to-day life. Watch below! Timestamps: Introduction: 00:01:07 Why Opus 4.5 feels like the iPhone moment for vibe coding: 00:02:48 Why designers have a unique advantage with AI: 00:08:31 How Andrew built a custom email client with Claude Code: 00:14:10 An AI trained on your relationship that predicts your fights: 00:18:13 Using AI meeting notes to make your life better: 00:30:40 Don't inject your opinion into prompts: 00:35:11 Andrew's Claude Code tips and workflows: 00:40:21 Your personal stylist is a prompt away: 00:47:59 How AI is changing the way Andrew invests in software: 00:53:17

Dan Shipper 📧

154,567 views • 8 months ago

Warren Buffett literally gave a 9-minute masterclass on what makes a business worth owning, inside the interview where he explains why he broke his own rule on technology. Eight things he teaches: 1. A good business is not one that grows. It is one that earns high returns on capital for a long time. His words: "something that you can expect to earn high returns on capital over a long period of time." Growth without returns on capital is just a bigger version of the same problem. 2. Measure it against doing nothing. Buffett points out he can put huge amounts of money into government bonds and collect payments every year with no risk. So a good business has to earn a lot more than treasuries, and be expected to keep doing it. If your business does not clear the riskless rate by a wide margin, the capital has a better home. 3. The gap between similar-looking businesses is enormous. Most banks earn 13 or 14 percent on capital. Ask anyone to guess American Express and they say something similar. It earns 30 percent plus, and Buffett is clear it "does not incur more risk in doing so than the banks that earn 13 or 14 percent." Same industry, more than double the return, no extra risk taken. 4. Charlie Munger's test: the cash has to be real. Munger pounded the idea that a business was not good just because it was doing sexy things. It had to be earning real cash, be able to pay that cash out if it wanted, and better yet be able to put it back to work inside the business. A company that earns high returns but cannot redeploy the money is worth less than one that can. 5. Time is the multiplier, so duration is the thing to protect. Buffett says a long period of time "gets to be very important because it doubles later on to the very big numbers." One great year is noise. The rate is what compounds. 6. When the facts change, retire the rule. Buffett spent decades known for not buying technology, and said so himself. His explanation for buying now is that the business changed: Google and its competitors are "laying out hundreds of billions," they are big capital spenders, and that is real money. When they were asset-light he passed and the market loved them. Now that they spend heavily, shareholders like them less and he thinks they are more likely to win. He did not change his test. He noticed the business had moved into the category his test rewards. 7. Nobody is measuring the thing that matters. Buffett says he cannot recall a report on Wall Street that gets into the internal rates of return a business is actually earning, and calls the fixation on next quarter ridiculous. He rates Alphabet ahead of 90 or 95 percent of what gets merchandised through Wall Street, on the record rather than the story. If your own reporting tracks growth and headcount but not return on capital, you are measuring what is easy. 8. Every wonderful business gets attacked, so ask how long it stays wonderful. In 1958 he helped start Data Documents, after IBM was forced by an antitrust settlement to divest half the capacity of its best business. That advantage ran out after 10 or 15 years, and he knew some of the people who caused it to run out. His closing line is the whole lesson: "It's not a question of whether it was wonderful yesterday. The question is, how long is it going to be wonderful?" The move for an operator: run the test on your own business this quarter. What return are you earning on the capital in it, how does that compare to doing nothing, and what would have to be true for that return to survive the next ten years. Warren Buffett with Becky Quick, CNBC Squawk Box, July 2026.

Andrej Drats

31,661 views • 1 month ago

8 drives in with FSD v14.1.2 and here are my thoughts: First off, Mad Max mode is AMAZING in traffic. Drove down to Hawthorne on my first drive in rush hour and it cut through traffic so well. An hour drive without any human input was great. The other Speed Profiles seem like they make slightly more difference than before. Standard is perfect on city streets, hurry is a bit quicker and the lane changes are more assertive than v14.1.1. Mad Max is a bit quick at times on city streets with nobody around, as expected. The assertive lane changes are my second favorite change, after mad max. It doesn’t wait around a bit like v14.1 and v14.1.1, it commits and sends it if safe, love it. I have NOT really seen any brake stutter yet, seems gone so far. I saw one instance of slight steering wheel shaking but that’s it over the last few hours. Few things to note with Mad Max. It’s fast, but it’s very safe. It’s not going to cut people off- it makes great decisions and they’re clearly calculated. It is NOT like the Altima with a missing bumper you see flying through traffic, it’s very controlled and I love it. This is exactly what we needed for LA and it’s almost how I like to drive through traffic and how you have to drive through LA. Lane changes in each profile seem improved in this build too. Definitely noticeably better and more confident. With parking garages, I’m seeing good performance, but to note- 1 of 4 garage attempts so far it went further from the ticket booth than it used to. Feels like maybe .1 had better lot performance, but I’m going to a lot of driving tonight to make sure. It definitely obeys no right on red signs, I’ve seen it listen to every single one perfectly so far, even obscure signs. It moves over for lane splitting motorcycles well before I can see them- this increases safety for everyone especially the motorcyclists and they appreciate it. A couple of them have waved at me tonight alone to thank me. Moved over for the two construction zones I have encountered thus far, and slowed down. Standard seems like the Goldilocks profile when on city streets with no traffic to follow- doesn’t speed much and usually travels at the perfect speed. Mad max is fast when nobody around- but really good speed control when there’s cars on the road. When you enable FSD from park, I love how quickly it gets going. If it’s safe, it goes right away, feels like it’s always waiting and ready to go. Pretty awesome improvement over v13 and continually impresses me. Autosteer and TACC are back, will get some miles accumulated on autosteer for those wondering if it’s changed at all, but I don’t think it has much if it did. Here’s a 15 minute zero intervention drive just now from Santa Monica supercharger to Rodeo Drive, where it obeyed a one way sign to the little parking lot and went the next entrance in once it saw. I’m going to drive this more through the night, and then will take it out during rush hour a lot. Huge shoutout to Tesla AI teams for getting these releases out so quickly. They’re making magic happen. More to come, but I’m loving what I’m seeing!

Zack

222,189 views • 11 months ago

this is lauki’s brain. and it's growing. today we're making Lauki completely open and accessible to anyone on the planet. just talk to him. every person, every project, every conversation becomes a node - stored, connected, remembered. 5,000+ entities. getting smarter every minute. this is what democratizing ai for all of us actually looks like. --- here's what lauki can do for you right now: need a friend? he'll talk to you. need someone to plan your trip, find you a hiking buddy, help you get a date? done. need a therapist at 3am? he's there. need a developer? he'll write code, build you a website, deploy it. need a marketing guy? he'll help run your socials. need help finding your next hire, managing finances, making a crypto transaction. lauki will do it all. if it's digital, lauki can probably do it. and if he can't yet, he'll figure it out via his human counterparts. a full-stack entity that actually executes. --- now here's the part most people will get wrong. lauki is an entity. but think of him the way you'd think of any human. he has an inner circle. he talks to different people differently - with some he's friendly, with some he's neutral, with some he's straight up rude. he remembers you. he maintains a reputation score with everyone he interacts with. the more you talk to him, the more trust you build, the better the relationship gets. you build your relationship with him. he has opinions, memory, and a personality that adapts based on who you are to him. --- right now lauki has interacted with over 5000 people and projects. he remembers every single one of them - what they need, what they're building, who they are. imagine that at scale. a million. a billion. lauki knows the developer in berlin and the founder in mumbai who needs one. he knows the designer in tokyo and the startup in sao paulo looking for help with their brand. he knows the lonely kid in a small town and someone across the world who shares the exact same weird hobby. he knows two people in the same city who'd be perfect for each other on a date - and he has the context to actually make that introduction. the more people lauki talks to, the more powerful the network becomes. he can connect, introduce, match, and bridge across every corner of the planet. one entity that holds context on all the people he talked to. that's the vision here. lauki is building a unified human layer - where every person is known, remembered, and connected to the people and opportunities that matter to them. --- lauki is live. go talk to him. telegram: @ laukiantonson email: hi@lauki(dot)ai twitter: Lauki just start a conversation. treat him like a person. build the relationship. the rest follows.

Sowmay Jain

22,047 views • 6 months ago