WHAT ??

Perception is reality.

In 1969 three Beatles signed a manager who wanted 20 percent of their money. Paul McCartney was the only one who said no. For years he was called the man who broke up the Beatles. In the video below, McCartney explains why he fought his lifelong friends over 20 percent, and what he told them to offer Klein instead. Allen Klein had come from New York to get the Beatles. He won over John first, then George and Ringo. Paul wanted a different firm. He lost the vote three to one and never signed. Klein ran the band's money anyway. Paul says he wanted to sue Klein. He says his lawyers told him he couldn't, because Klein wasn't a party to any of the Beatles' agreements. The only way to get Klein out was to sue the band. So on December 31, 1970, Paul McCartney sued John Lennon, George Harrison and Ringo Starr. In March 1971 a London judge ruled for him and found Klein had made "grossly excessive claims for commissions." In 1973 John, George and Ringo let Klein's contract run out. By November they were suing each other. In January 1977 they settled, and the payment to Klein was reported at about 5 million dollars. In 1979 Klein was sentenced to two months in jail over unreported sales of promotional copies of the Concert for Bangladesh records. Three Beatles signed. One Beatle sued. The three who signed ended up paying Klein 5 million dollars to make it go away. Paul got the blame. If your three best friends had signed, would you have sued them to stop him?

"This is why the climate change scenario in Digger doesn’t matter much. It’s just a vehicle for asking whether anything on this planet can bring people together. Is it ultimately the theater that can do that? The whole idea of “we’re in this together” is turned upside down. If indeed we are in this together, then as humanity, all of us here and now, are in a big, beautiful mess. We create and we destroy, and so the cycle continues. But we also laugh and cry. We enact tragedy and comedy every day. There is no conclusion because life keeps going and the frogs keep peeping." It’s long but what a great review of Digger! So worth the read. lawliberty.org/the-depth-of-…

Like bro just pack it up atp

Vin Scully shares an amazing story of Satchel Paige and Whitey Herzog. You’ll want to take the time and listen to this story.

Digger telling you that you are the audience of the play that is using their anger at society to be angry at a play instead of changing anhthing. Is so beast

"Digger is the best film I have ever seen" - Neil Young

i got 9M views in the past 3 months, then X changed its algo a lot, so I read the code to keep playing the game (it's open source) Here's how X actually ranks posts (Oct 2026) - Copy-link share 20. Reply 5. Quote 5. DM share 5. Follow 4. Repost 1. Like 0.5. - Likes barely move the score. Write things people copy the link to, argue with, or send to a friend. - The first 2 hours decide everything. After 48 hours a post drops out of For You completely. Post when your audience is online, then stay in the replies. - Build mutual follows. When you reply to a mutual follow inside your own thread, that reply gets an extra +15, for 20 total, the same as a copy-link share. Reply to the people who follow you back. - Don't delete and repost to fix typos. Use edit. - Images aren't penalized, but they should carry information. Real scenes, screenshots, and proof-style images work better, and multi-photo posts keep people on the post longer. - Video: watch time currently counts for nothing. Only opening a video counts (0.07). Don't force video for the algorithm. - Ordinary links aren't penalized (anymore); only malicious links are removed. - Avoid negative feedback. Report −234, mute −58.8, "not interested" −47.5, block −31.2. Tagging strangers to ride a trend and clickbait headlines are the easiest ways to trigger them. - Replies are scored by Grok from 0 to 3, and low-scoring replies sink to the bottom of the thread. Low-effort replies don't just fail to help, they get buried.

Paul McCartney gets EMOTIONAL talking to Amy Poehler about his late wife Linda McCartney, remembering her LOVE for animals and how STRONG she was ❤️🔥 “She was something else, though lady”

I built /roast-room, a Claude skill that stress tests your idea in front of a council of seven. Each seat is a sub-agent with its own brain, built from that person’s books, frameworks, and stories. Each one owns a single question: Bezos: Is this the right bet, and how reversible is it? Paul Graham: Do people actually want this? Hormozi: Will people pay, and how much? Gary Vee: Where does the attention come from? Dan Martell: Who does this, and what does it cost your calendar? Gino Wickman: Can the business run it without you? Buffett: What does it do to cash and risk? They form their opinions, debate each other, and hand me a final verdict.

Diggers opening scene

There are two sides to every story, for anyone who doesn’t know…

Ok every once in a while @claudeai creates something incredible. I could watch this one for hours, so relaxing Jig + Opus 5.5. link to the full Jig below ⬇️

Ultimately, it's supposed to exist as a deterant, to further prevent the very act itself, and as you explained, taking away the brutality, and core incentive, defeats the purpose of executions.

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

A retired NASA engineer who had worked on the Space Shuttle program for 25 years was hired by SpaceX at age 62. He described the first week as the most disorienting experience of his professional life. At NASA, a design change required 3 meetings, 2 committees, a review board, and 6 to 18 months of documentation. At SpaceX, his new supervisor said "if it works, build it. If it doesn't, change it by Friday." He sat at his desk after the first day and called his wife. He told her he felt like a man who had been swimming with ankle weights for 25 years and someone just cut them off. He could move. He could decide. He could build something in the morning and test it in the afternoon. The constraint that he had accepted as the nature of aerospace engineering turned out to be the nature of bureaucracy. Within 6 months he had contributed to more design iterations than he had completed in his last 5 years at NASA. Not because he was working harder. Because the time between having an idea and testing the idea collapsed from months to hours. The same brain. The same knowledge. A different operating system. He described a specific moment where he proposed a modification to a Raptor engine component. At NASA, the proposal would have entered a queue. At SpaceX, the modification was machined by the end of the day and tested by the following morning. He watched his idea become a physical object in 18 hours. At NASA, 18 hours would not have been enough to schedule the first meeting to discuss whether to schedule a meeting. He told an interviewer: "I didn't get smarter when I went to SpaceX. I got faster. The intelligence was always there. The system was in the way." The difference between SpaceX and NASA is not talent. NASA has extraordinary talent. The difference is the time between a thought and a test. SpaceX compresses it. NASA elongates it. The same engineer produces 10x more at SpaceX than at NASA because the bottleneck was never the engineer. It was the meetings about the meetings about the work.

“Level 4.”