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Veltrx

@Veltrxai

AI updates, tools & breakdowns.

AI... Katılım Mayıs 2026
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Veltrx
Veltrx@Veltrxai·
Sam Altman: "You can identify founders who have a chance at creating a $10 billion company. With practice." Then he shared the experiment that proved it. YC funded 20 teams of strong founders without ideas. All 20 failed. > real founders generate new ideas every week, not one big one > execution speed between meetings predicts success better than anything on paper > a founder improving fast over 2 months he's been right ~10/10 times on this signal > the core four: obsession, focus, frugality, love everyone screens for intelligence. almost nobody screens for slope. which one would you bet on?
West Lord@MyWestLord

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Veltrx
Veltrx@Veltrxai·
Sam Altman taught Stanford exactly how to hire and execute in "How to Start a Startup" Lecture 2 is 45 minutes and free. Inside it, the numbers hit hard. 9 startups in 1 YC batch added random co-founders all 9 were dead within 12 months, while every one of the top 20 most valuable YC companies had at least 2 founders. His hiring math is brutal: Airbnb spent 5 months interviewing employee #1 and hired only 2 people in year 1, because 1 mediocre hire in the first 5 can kill the entire company, and Brian Chesky asked candidates if they'd still take the job with 1 year left to live. His equity rule flips what most founders do 10% of the company to the first 10 employees, fight the investors instead, because the YC companies most generous with early equity became the most successful ones he funded. His execution rule is 1 number: a viral coefficient of 0.99 flatlines forever, 1.01 compounds forever, and the gap between them is a little extra work on the right thing. And when his own startup was losing its first big customer to an older competitor, he didn't send a deck he got on a plane that night, sat in their lobby from 6 AM until someone cracked and agreed to talk, and closed the contract 1 week later. This is the class Stanford charges $60,000 a year for. The whole lecture sits on YouTube for $0.
Veltrx@Veltrxai

Sam Altman taught 720 startups one formula where luck is a random number between 0 and 10,000. Stanford, 2014. The opening lecture of CS183B was so packed he asked for a bigger auditorium. He was 28, a dropout from this same school 9 years earlier, now running Y Combinator. The formula he wrote on the board: idea × product × team × execution × luck and you only control 4 of the 5, because the fifth one goes to 10,000. His words, not a metaphor. Then he did something strange: he handed half of his own lecture to Dustin Moskovitz, co-founder of Facebook, whose entire job was to talk students out of starting companies. Dustin showed one table. Employee 100 at Dropbox with standard 10 basis points made $10 million, employee 250 at Facebook made $200 million, and employee 1,000 joining in 2009, when everyone said it was too late still made $20 million. Your own startup? Best case you build a $100 million company and keep 10% after dilution. $10 million, same as employee 1,000, minus your health. Dustin knew the price because he paid it: at 21 he was throwing his back out every 6 months from pure anxiety, always on call, unable to quit a founder who leaves wears the black eye for a decade. Then Altman twisted the lecture back with advice that cut against everything in the room. The best ideas look terrible at the start: the 13th search engine, the 10th social network limited to college kids, sleeping on strangers' couches. If an idea sounds good, too many people are already building it. Make something 100 people love instead of something 10,000 people like. Ben Silbermann recruited Pinterest's first users by walking up to strangers in Palo Alto coffee shops, then resetting every browser in the Apple Store to Pinterest's homepage until they threw him out. And the only valid reason to start is that you can't not do it. Dustin built Asana at night, after full days at Facebook, unpaid and unasked. "The idea was beating itself out of our chest." The rest is a number between 0 and 10,000.

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Veltrx
Veltrx@Veltrxai·
Sam Altman told a Stanford security class which AI field is the most undervalued in 2026 and it isn't building models. Dan Boneh asked him where students should go, and Altman pointed straight at AI security. His logic runs on 2 features everyone loves right now. Feature 1 — models that know you. Your chat history, your health issues, your connected data, all inside one personal model. Feature 2 — models that act for you. They browse, they buy, they call other services on the open web. Put them together and you get a model that knows everything about you while talking to strangers. Altman's example: you tell it about your private healthcare problems, then send it shopping and the e-commerce site should never learn what your doctor knows. Your spouse understands which secrets stay home. The model doesn't, not yet, and solving that with 100% robustness is an open problem nobody owns. Meanwhile Google and Amazon run thousands of engineers on platform security. AI labs are only starting to build those teams, which means the demand curve is about to bend hard while the supply of people who understand prompt injection, adversarial robustness and model extraction stays tiny. Altman went further: within a few years he expects a superhuman AI security analyst software that finds the bugs before you ship, and the same capability powering cyberattacks from the other side. Everyone is racing to build AI. Almost nobody is guarding it.
West Lord@MyWestLord

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Veltrx
Veltrx@Veltrxai·
Sam Altman screened 20,000 startups a year at Y Combinator, where all 8 of the only accelerator companies ever to hit $1B came from. Out of 2,500 accelerators on Earth, one produced every single winner and this is what he says actually separates the founders who make it. Speed beats everything, even determination. Decision speed correlates almost exactly with success across every YC winner, while slow but determined founders fail anyway. Hiring is a trap. The best YC startups hire the least Airbnb took 9 months to hire employee #1, Stripe about the same, because every early hire adds burn rate, politics, and inertia you haven't earned. The Airbnb founders were so broke they kept maxed-out credit cards in plastic baseball card sheets while rent was due in 10 days. Brian Chesky rented his spare room for the exact gap, and that desperation became a $100B company. Only 2 kinds of pivots ever work: The thing you wanted to build all along Instagram was a dying app called Burbn until Systrom built the photo tool he actually loved. The thing you found by accident Slack was a dead game studio whose internal chat tool turned out to be the product. Whiteboard pivots, where founders brainstorm a new idea after the first one dies, work 0% of the time. Altman never saw one succeed. The #1 mistake great founders make is waiting too long to fire, and every great founder makes it. Altman found every fired person a new job before they left but he never un-decided. The $1B valuation on your offer letter is fiction, since liquidation preferences make the sticker number meaningless. He said it flat: intermediate valuations mean nothing. His last rule covers all of it. Ignore everyone except your users.
West Lord@MyWestLord

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Veltrx
Veltrx@Veltrxai·
Sam Altman taught 720 startups one formula where luck is a random number between 0 and 10,000. Stanford, 2014. The opening lecture of CS183B was so packed he asked for a bigger auditorium. He was 28, a dropout from this same school 9 years earlier, now running Y Combinator. The formula he wrote on the board: idea × product × team × execution × luck and you only control 4 of the 5, because the fifth one goes to 10,000. His words, not a metaphor. Then he did something strange: he handed half of his own lecture to Dustin Moskovitz, co-founder of Facebook, whose entire job was to talk students out of starting companies. Dustin showed one table. Employee 100 at Dropbox with standard 10 basis points made $10 million, employee 250 at Facebook made $200 million, and employee 1,000 joining in 2009, when everyone said it was too late still made $20 million. Your own startup? Best case you build a $100 million company and keep 10% after dilution. $10 million, same as employee 1,000, minus your health. Dustin knew the price because he paid it: at 21 he was throwing his back out every 6 months from pure anxiety, always on call, unable to quit a founder who leaves wears the black eye for a decade. Then Altman twisted the lecture back with advice that cut against everything in the room. The best ideas look terrible at the start: the 13th search engine, the 10th social network limited to college kids, sleeping on strangers' couches. If an idea sounds good, too many people are already building it. Make something 100 people love instead of something 10,000 people like. Ben Silbermann recruited Pinterest's first users by walking up to strangers in Palo Alto coffee shops, then resetting every browser in the Apple Store to Pinterest's homepage until they threw him out. And the only valid reason to start is that you can't not do it. Dustin built Asana at night, after full days at Facebook, unpaid and unasked. "The idea was beating itself out of our chest." The rest is a number between 0 and 10,000.
West Lord@MyWestLord

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Veltrx
Veltrx@Veltrxai·
Sam Altman raised $110B in 1 round while the biggest IPO in history only ever raised $25B The man interviewing him runs BlackRock and sits on OpenAI board. He opened with it: Sam is a friend, and he promised not to throw only softballs. Then the numbers started. 900 million users. Amazon, Nvidia and SoftBank in a single round. A gigawatt campus in Abilene, Texas with 10,000 workers on site "looks like a spaceship inside." Training what Altman calls the best model in the world, hopefully by a lot. 16 months ago o1 shipped. The same answer today costs 1,000x less. His timeline: by late 2028 more of the world's thinking sits inside data centers than outside them. India: Codex usage 10x'd in months. He read the briefing sheet and assumed it was a bug. Founders there told him they're past 1-person startups they want 0-person startups. Write 1 prompt, go on vacation. Then he described the ending himself. Quality of life goes up. GDP goes down. Forever. "I don't know what it means to live in a forever deflationary world." His fix is already in fabrication: an OpenAI inference chip, not the fastest but the cheapest per watt, deployed at scale by December. Built for agents that never sleep. He says intelligence should be "too cheap to meter." Like water, like electricity sold by the token, from his data centers, on his chips. 2 men on 1 stage. 1 runs the money, 1 runs the machines, both sit on the same board. He wants to flood the world with intelligence. He owns the flood.
West Lord@MyWestLord

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Veltrx@Veltrxai·
this free 1-hour Stanford lecture covers more than most $500 "AI engineer" courses: > why fine-tuning is usually a trap (and the 2 cases it isn't) > prompt chaining that lets you debug like software > RAG explained so simply it's a common interview question answer > how to eval agents: objective vs subjective, component vs end-to-end > multi-agent systems when parallelism actually justifies them CS230, taught at Stanford, uploaded for free. watch it today, link below
West Lord@MyWestLord

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Veltrx@Veltrxai·
MIT professor Patrick Winston: "If you get the representation right, you're often almost done." this one lecture from MIT AI course explains more than most $500 prompt engineering courses > naming a thing gives you power over it (he calls it the Rumpelstiltskin principle) > "simple" and "trivial" are not the same MIT people miss opportunities confusing them > a rule-based system from the 80s still saves Delta ~$500K a day parking planes > language is the thing that separates us from chimps, not raw compute everyone is tuning prompts. Winston solved the real problem decades ago. full lecture below
West Lord@MyWestLord

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Veltrx@Veltrxai·
Elon Musk sat next to Sam Altman in 2016 and praised the nonprofit they built to keep AI out of the hands of a few. Altman ran the camera. He asked how the 6-month-old company was going. Musk called it a talented team. A 501c3. A charity to democratize AI "so it doesn't get concentrated in the hands of a few." That was the whole pitch. Keep it open. Keep it shared. Keep it out of any single grip. 10 years later, that charity is worth over $800B and filing for a $1T IPO. The nonprofit grew a for-profit arm. Microsoft took a stake. Altman ran all of it. In 2024, Musk sued for $150B . He wanted Altman removed and the structure torn down for breaking the exact promise he watched him make on camera. On May 18, 2026, a jury threw it out in under 2 hours. Filed too late, they ruled. Now he calls him "Scam Altman." 3 days ago Apple sued OpenAI. Musk piled on. Altman's reply: the surest sign his model is winning is that Elon is obsessed with him again. 2 co-founders. 1 charity. 11 years. They filmed the whole thing themselves.
West Lord@MyWestLord

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Veltrx@Veltrxai·
Jensen Huang told a Stanford room that Nvidia beat Moore's Law by 1,000,000x in 10 years. Moore's Law promised 10x. To get there he made a bet that looked insane. The most expensive computer ever built cost $350 million. That was the ceiling, the largest scientific supercomputer on earth. He decided to build one worth multiple billions, for a market of exactly 0 customers. Nobody had ever spent that on a machine. He knew it and built it anyway. Then the researchers saw the speed and said forget curating data, just feed it the whole internet. That one machine is why ChatGPT exists. Here's the part nobody quotes. Nvidia's first product was wrong. Not a little wrong. Curved surfaces instead of triangles, no Z buffer, no floating point. They burned 2.5 years and nearly died 4 times. The kid who built it used to bus tables at Denny's. Now every self driving car, every CT scanner, every AI lab on earth runs on his chips. He didn't predict the future. He built the machine that forced it.
West Lord@MyWestLord

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Veltrx@Veltrxai·
NVIDIA CEO Jensen Huang, on stage at Stanford: "Is coding going to guarantee you a job? No. Not even a little bit." then he said the part everyone missed: 10 million people are employed because they can program the other 8 billion got left behind "in the future, we all can program computers" English is the best programming language of the future the skill that made people rich for 30 years just became the default setting. what do you tell a CS freshman in 2026?
West Lord@MyWestLord

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Veltrx@Veltrxai·
Anthropic CEO on live TV: "We can't stop the AI bus. But we may have an opportunity to steer it." then he said the part nobody in the industry says out loud: entry-level white collar jobs in finance, consulting and tech get replaced first timeline: 1 to 5 years, not decades unemployment could spike to 10-20% AI CEO already discuss this in private. the public just isn't told the man who builds the thing is asking congress to regulate the thing. Watch the interview, then decide if he's early or just honest.
West Lord@MyWestLord

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Veltrx@Veltrxai·
The guy who coined "vibe coding" just said it's already over. Andrej Karpathy: "vibe coding raises the floor. agentic engineering raises the ceiling and the ceiling is way higher than 10x." his new framing, in his own words: > vibe coding = everyone can build anything, quality optional > agentic engineering = same speed, but you own every vulnerability > agents are "spiky interns" powerful, fallible, stochastic > your job is coordinating them without dropping the quality bar > the best people at this "peak a lot more than 10x" one year. that's how long the trend he started lasted before he moved past it. what do we call people still stuck on vibe coding?
West Lord@MyWestLord

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