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The difference between Elon and this reporter: Elon builds things millions of people use, love and benefit from All this reporter produces is fake news: selective facts, dishonest framing and propaganda disguised as journalism Just listen to her shouting throughout the interview. It looks less like journalism and more like watching a leftist protester being asked, “Which rights are you protesting for?”......only to reply, “Am I supposed to know that?” One creates real value. The other manufactures fake outrage Trust in legacy media has hit an all-time low. No wonder nobody trusts them anymore 𝕏 is where truth wears the crown 👑

Did you know Calendly founder Tope Awotona had already tried several business ideas before Calendly? Those earlier ventures did not become breakout successes, but they were far from wasted 🔥 Each attempt exposed him to different customers, different problems, and different lessons about what people truly valued. Many first-time founders treat an unsuccessful idea as proof they are not cut out for entrepreneurship. One disappointing launch or failed experiment becomes a verdict on their ability instead of another step in developing it 🤯 But the real value of an early business idea is often what it teaches you. Every experiment helps you better understand customer pain, buying behaviour, market timing, and the kinds of problems people are genuinely willing to pay to solve. 💡 After every business venture you tried, ask yourself: → What surprised me? → How did customers actually respond? → What would I do differently next time? Then carry those lessons into your next idea instead of starting from zero again. Every thoughtful experiment makes you a more capable founder. Over time, those lessons improve your judgement, sharpen your decisions, and increase your chances of building the business that finally takes off. As always, keep going and growing. 👉 Follow @bMightie for more founder intelligence for solo founders and bootstrapped businesses on the journey from day zero to takeoff. #founderstory# #startupstory# #founderjourney# #founderlife#

The great lie is that society is divided between rich and poor. The great truth, as David Friedberg puts it, is makers vs takers. Makers build, create, and deliver real value: houses, software, art, businesses, and everything that moves civilization forward. Takers watch, criticize, analyze, and politic. They push the lie that the rich hoard unfairly so the poor must seize it… all while positioning themselves to rule the chaos. As @friedberg tells his kids: “At the end of the day, if you made something and someone else valued it, you were a maker. That was an amazing achievement. That is a great day.” Takers thrive on division. Makers drive progress. Time to choose your side.

Nixon defaulted and broke world's monetary system in 1971 because the combined costs of the Great Society and the Vietnam War had become impossible to fund with sound money. Greenspan eased through every crisis of the 1990s and early 2000s because the political cost of a real recession was impossible to pay. Bernanke monetized the housing collapse of 2008 because a true deleveraging of the American household would have been impossible to survive politically. Powell monetized the pandemic of 2020 because the precedent of the previous three acts eliminated any other option. Each man inherited less room to maneuver. Each man, when forced to choose, chose to make the room smaller still for the man who would come after him. That is what a monetary death spiral looks like. It does not arrive in a single day. It does not announce itself on the news. It is a series of small, defensible decisions, each one reasonable at the moment it is made, each one making the next decision harder to avoid, until one morning the country wakes up to discover that there are no decisions left. That’s why the dollar has lost more than 90% of its value against gold since 1971. That’s why federal debt held by the public has crossed $36 trillion — more than 120% of GDP. That’s why net interest on the national debt is now the largest line item in the discretionary federal budget. Larger than defense. Larger than veterans’ benefits. Larger than everything except Social Security, Medicare, and Medicaid — and growing faster than any of them. And that’s why the stock market has lost 77% of its real value, measured in ounces of gold, since August 1999. Even though they may not be able to articulate exactly why, that is also why a majority of the prime-age men in this country — the men who built every previous version of America, the men on whose shoulders every future version of America will have to be built — have correctly concluded that the scoreboard has been rigged against them for their entire working lives, and have responded, with perfect economic rationality, by reducing their participation in the rigged game. What is coming in 2029 is not a new crisis. It is the compound interest on the decision Richard Nixon made on a Sunday evening in August of 1971. The math was set in motion 54 years ago. We are, all of us, living out the back end of an equation whose answer was fixed on the weekend Nixon flew home from Camp David. The only remaining question is: what you are going to do about it. The good news, and it is genuinely good news, is that in every previous case of this kind of monetary decay, the decay has ended. Always. Sometimes in revolution, sometimes in restoration, sometimes in both. The American Republic has already been through three Fourth Turnings — the Revolution of 1776, the Civil War of 1861, and the Depression-and-War era of 1929–1945 — and it has come out the other side each time, battered but rebuilt, with a new and sounder monetary order. There is nothing in the American character that prevents it from doing so again. The people who will rebuild it after 2029 are alive right now. Some of them are reading this book. The question is whether you will be one of them — or one of the people who are wiped out by what’s about to happen.

Elon Musk thinks the entire education system is built on a broken assumption. That every student should learn the same thing. At the same speed. In the same order. At the same time. Musk: “Everyone goes through from like 5th grade to 6th grade to 7th grade like it’s an assembly line. But people are not objects on an assembly line.” The model was designed for a factory economy. Standardized inputs. Predictable outputs. That economy is gone. The assembly line is gone. But the education system still runs on its logic. A student who masters algebra in two weeks sits through eight more weeks because the calendar says so. A student who struggles gets dragged forward because the schedule doesn’t wait. Neither is being served. Both are being processed. Musk: “Allow people to progress at the fastest pace that they can or are interested in, in each subject.” AI doesn’t teach a classroom. It teaches a student. One at a time. Every time. It skips what a student already knows. It finds where they’re stuck and approaches it from a different angle. It adjusts in real time. Not at the end of a semester when the damage is already done. A student obsessed with basketball learns fractions through shooting percentages. A student who builds in Minecraft learns geometry through architecture. The subject doesn’t change. The entry point does. No teacher with thirty students can do this. Not because they lack skill. Because the math doesn’t work. AI doesn’t have that constraint. Musk: “You do not need to tell your kid to play video games. They will play video games on autopilot all day. So if you can make it interactive and engaging, then you can make education far more compelling.” The brain isn’t broken. The format is. Kids learn complex systems and strategic thinking for hours voluntarily. Then walk into a classroom and can’t focus for twenty minutes. That’s not a discipline problem. That’s a design problem. Musk: “A university education is often unnecessary. You probably learn the vast majority of what you’re going to learn there in the first two years. And most of it is from your classmates.” Four years. Six figures of debt. And the real value comes from the people sitting next to you. Not the institution charging you. The degree doesn’t certify knowledge. It certifies endurance. Musk: “If the goal is to start a company, I would say no point in finishing college.” The system was built to train employees. If you’re not trying to be one, it has nothing left to offer you. Every lecture. Every textbook. Every curriculum. Now available instantly. Personalized to any learner. Adapted to any pace. The question isn’t whether the old model survives. It’s how long we keep forcing students through it while the replacement already exists.

Everyone’s spinning up a new L1 these days. Most feel like slight variations on the same theme. What stands out about @NomismaNetwork is the bigger picture they’re actually building a system where AI agents, economic coordination, and real value creation aren’t siloed experiments, but native parts of the same environment. Not just another chain trying to be faster or cheaper. More like infrastructure designed for AI native economies and useful DeFi coordination in one place. Still very early, but the direction feels genuinely forward looking instead of hype driven. Worth watching.

Stop guessing which models fit in your VRAM! llmfit is a CLI tool that auto-detects your hardware and ranks 206 models by what actually runs on your system. You download a 70B model and hope it fits. Or you estimate memory requirements across quantization levels and still end up with models that crash or run too slow. llmfit changes that. It detects your CPU, RAM, GPU, and VRAM, then scores every model in its database against your hardware. Instead of assuming one quantization level, it tries the best quality that fits. Starts with Q8_0, walks down to Q2_K if needed. If nothing fits at full context, it tries half context. You get the highest quality model that actually works. Each model gets scored on Quality, Speed, Context, and Capability. The weights shift based on what you're doing. Chat models prioritize speed, reasoning models prioritize quality. Run it as an interactive TUI to browse models, use CLI mode for a quick table, or get JSON output for scripts. There's a REST API for cluster schedulers. You can also run it in reverse. Give it a model you want to run and target performance, it tells you what hardware you need. The real value: you see ranked options before downloading anything. No more burning bandwidth on 50GB models that won't run. It's 100% open source. Link to llmfit in comments!

Gm, Unis. I’ve been deep in the product every day, making a thousand small changes, testing details, and trying to build something that can actually survive after launch - not something that looks clean on mint day and disappears by week two. Here’s the part most people avoid saying: NFT projects usually don’t die because the art is bad. They die because there is no system behind them. No traffic engine, no content flow, no way to keep attention moving once the first wave is gone. Founders burn out, hire people they can’t really manage, and slowly the community goes silent. That is the problem we are building around. The LMM behind UniPix is designed to support the operational layer of a project: traffic, audience conversion, X presence, WL/GTD analysis, community signals, and the daily routine work that usually drains founders. It helps us see patterns earlier, understand who brings real value, and avoid building around people who are only here to extract and leave. UniPix is not just a collection you mint and forget. It is access to a system that keeps working after launch day. The model gets sharper with use. The product keeps moving. And I think the next cycle will make this obvious: the projects still alive months after mint won’t just be the ones with the loudest launch. They’ll be the ones with a real system behind them. That is what UniPix is building.