Ethan

[Ethan @EthanXvip]

Built an AI agent in 20 minutes and Anthropic bought it for $100k. Then at Stanford they showed exactly how to pull it off again from scratch:

02:00 - building your first agent on Opus 5 in 20 minutes
22:34 - one agent doing the work of an entire $200k/year Anthropic engineering team
49:47 - turning that into $1.2M/year selling agents to Anthropic and Google

I watched it, spent 20 minutes in Claude Code, and the agent I built replaced 10 Anthropic engineers. They paid $100k for it and came back asking for more.

Bookmark this and watch. The article below walks through building an agent in Claude Code in 20 minutes and scaling it to $1.2M/year.

[Ethan @EthanXvip]

Built an AI agent in 20 minutes and Anthropic bought it for $100k. Then at Stanford they showed exactly how to pull it off again from scratch:

02:00 - building your first agent on Opus 5 in 20 minutes
22:34 - one agent doing the work of an entire $200k/year Anthropic engineering team
49:47 - turning that into $1.2M/year selling agents to Anthropic and Google

I watched it, spent 20 minutes in Claude Code, and the agent I built replaced 10 Anthropic engineers. They paid $100k for it and came back asking for more.

Bookmark this and watch. The article below walks through building an agent in Claude Code in 20 minutes and scaling it to $1.2M/year.

[Ethan @EthanXvip]

Mike Rowe admits he lives on the budget of someone pulling in $200,000 a year, even though he's worth way more than that, and he's down to just 4 pairs of pants.

“I’m living right now like I make maybe a couple hundred grand a year. I own 4 pairs of pants and like 5 shirts, and most of those I stole from wardrobes on various shoots… I believe the more things you own, the more things own you.”

[Ethan @EthanXvip]

Mike Rowe admits he lives on the budget of someone pulling in $200,000 a year, even though he's worth way more than that, and he's down to just 4 pairs of pants.

“I’m living right now like I make maybe a couple hundred grand a year. I own 4 pairs of pants and like 5 shirts, and most of those I stole from wardrobes on various shoots… I believe the more things you own, the more things own you.”

[Ethan @EthanXvip]

A billionaire basically laid out how the whole economy works in 42 minutes, and did it better than most $200,000 MBA programs ever manage.

[Ethan @EthanXvip]

What clicked for me is that he didn't rely on predictions at all — just built a system to react to what's happening right now. That single mindset shift made me move from gut-feeling trades to running a quant bot. Way less stress, way more logic.

Been running it for a while now—if you're curious about the setup, drop me a message "NOW" and I'll share how it works

[Ethan @EthanXvip]

A billionaire basically laid out how the whole economy works in 42 minutes, and did it better than most $200,000 MBA programs ever manage.

[Quantex @Quantex0x]

https://t.co/a7RPR0Hlud

[Ethan @EthanXvip]

Hiring Tony Robbins today runs a million dollars for a single day.

This is a 21-minute recording made in his own living room more than 30 years ago. In it, he shows exactly how to get literally anyone to say yes. The same material people now pay a fortune for... completely free right here.

It's a rare, raw recording from back when he still wasn't charging millionaires just to sit in the same room as him.

When someone says no, they reach for one of two excuses: "I don't have the time" or "I don't have the money." Neither one is true.

The real reason is they still don't believe it's worth it. It's not a money problem. It's a state problem.

Tony teaches a move he calls "attack and confess." Instead of arguing against the objection, you confess your own:

"I had the chance to go six months ago and I put it off until two months ago. I can't even imagine how much time I wasted."

The room goes quiet. Nobody pushes back.

Then he puts the person on the "yes train." Each small yes builds on the last one. Until saying no at the end feels harder than just saying yes.

By the time it's time to sign, the person has already said yes five times without even noticing.

Just 21 minutes. In it are the exact two moves people pay a million a day for: how to read anyone's state... and how to shift it.

Most people spend years fumbling their way through sales. He sketched the whole thing on a flipchart in his living room in under half an hour.

A seat in that room cost $125. Today, sitting across from him costs a million dollars a day.

The tape is free right now. And the answer is right there in the video.

The "state problem, not a money problem" line hit me hard, actually — most of my bad trades weren't bad math, they were bad state.

Chasing a loss, forcing an entry because I felt like I had to do something. That's the real reason I moved to running a quant bot instead of trading by hand, it doesn't have a state to manage.

Been on it a while now, happy to walk anyone curious through how it's set up. DM me: "NOW".

[Alxcapital @Allx032]

https://t.co/6DRAVynFDi

[Ethan @EthanXvip]

Hiring Tony Robbins today runs a million dollars for a single day.

This is a 21-minute recording made in his own living room more than 30 years ago. In it, he shows exactly how to get literally anyone to say yes. The same material people now pay a fortune for... completely free right here.

It's a rare, raw recording from back when he still wasn't charging millionaires just to sit in the same room as him.

When someone says no, they reach for one of two excuses: "I don't have the time" or "I don't have the money." Neither one is true.

The real reason is they still don't believe it's worth it. It's not a money problem. It's a state problem.

Tony teaches a move he calls "attack and confess." Instead of arguing against the objection, you confess your own:

"I had the chance to go six months ago and I put it off until two months ago. I can't even imagine how much time I wasted."

The room goes quiet. Nobody pushes back.

Then he puts the person on the "yes train." Each small yes builds on the last one. Until saying no at the end feels harder than just saying yes.

By the time it's time to sign, the person has already said yes five times without even noticing.

Just 21 minutes. In it are the exact two moves people pay a million a day for: how to read anyone's state... and how to shift it.

Most people spend years fumbling their way through sales. He sketched the whole thing on a flipchart in his living room in under half an hour.

A seat in that room cost $125. Today, sitting across from him costs a million dollars a day.

The tape is free right now. And the answer is right there in the video.

The "state problem, not a money problem" line hit me hard, actually — most of my bad trades weren't bad math, they were bad state.

Chasing a loss, forcing an entry because I felt like I had to do something.

That's the real reason I moved to running a quant bot instead of trading by hand, it doesn't have a state to manage.

Been on it a while now, happy to walk anyone curious through how it's set up. DM me: "NOW".

[Ethan @EthanXvip]

In 1986 a guy got banned from every casino in Vegas for counting cards. So he flew to Hong Kong with $180,000 and switched to betting on horses instead. He walked away with almost $900 million.

That's Bill Benter. He figured horse racing was just another counting problem. Same math, just more moving parts.

He and a partner showed up with $180k and a computer. Benter spent years training that computer to guess one single thing, the real chance each horse had of winning. If his number beat the odds the bookies were offering, he bet. If it didn't, he passed.

That's the entire trick. Expected value.

EV = p · b − (1 − p)

Only bet when your win chance p, at odds b, is worth more than your chance of losing.

This recording was never meant to be some hidden gem. Nobody expected Professor Tsitsiklis to hand over the whole foundation in 45 minutes, but that's exactly what happens on that board. Students in that room pay over $80,000 a year to sit through it. Here it's free. Here it's genuinely free.

Every quant, every professional bettor, every hedge fund analyst started with this exact hour. Benter just watched it and actually did the homework.

Almost nobody knows this lecture even exists. Watch it before it gets pulled.

Benter's whole edge came down to one thing: let the model calculate EV, don't let gut feeling override the number.

That's basically the logic behind the quant bot I've been running for a while now — same idea, just applied to markets instead of horses.

Curious how it's structured? DM me: "NOW", happy to walk you through it.

[Ethan @EthanXvip]

In 1986 a guy got banned from every casino in Vegas for counting cards. So he flew to Hong Kong with $180,000 and switched to betting on horses instead. He walked away with almost $900 million.

That's Bill Benter. He figured horse racing was just another counting problem. Same math, just more moving parts.

He and a partner showed up with $180k and a computer. Benter spent years training that computer to guess one single thing, the real chance each horse had of winning. If his number beat the odds the bookies were offering, he bet. If it didn't, he passed.

That's the entire trick. Expected value.

EV = p · b − (1 − p)

Only bet when your win chance p, at odds b, is worth more than your chance of losing.

This recording was never meant to be some hidden gem. Nobody expected Professor Tsitsiklis to hand over the whole foundation in 45 minutes, but that's exactly what happens on that board. Students in that room pay over $80,000 a year to sit through it. Here it's free. Here it's genuinely free.

Every quant, every professional bettor, every hedge fund analyst started with this exact hour. Benter just watched it and actually did the homework.

Almost nobody knows this lecture even exists. Watch it before it gets pulled.

Benter's whole edge came down to one thing: let the model calculate EV, don't let gut feeling override the number.

That's basically the logic behind the quant bot I've been running for a while now — same idea, just applied to markets instead of horses.

Curious how it's structured? DM me: "NOW", happy to walk you through it.

[Lima @limalemonnn]

https://t.co/4IXjj22pjU

[Ethan @EthanXvip]

@Galileoxbt the button is the weak link, not the edge, brutally accurate

[Ethan @EthanXvip]

@eliffxb ngl the GEX walls thing is kinda beautiful, dealers basically drawing the map for you

[Ethan @EthanXvip]

@0xLoran noise doesn't hide signal, it impersonates it

[Ethan @EthanXvip]

A billionaire sat in a chair for 42 minutes and listed every psychological trap that makes people lose money. for free. the finance industry has spent thirty years pretending this recording does not exist.

he didn't sell a course. he didn't run a newsletter. he sat in a chair at 96 years old and explained why smart people do the stupidest things with their money. then he explained why they'll keep doing it anyway.

MBA programs charge $200,000 to teach behavioral finance. he walked through 25 biases in a single sitting. some of them still aren't in any curriculum. he handed over the whole framework on camera.

the part nobody mentions: he called crypto antisocial. said index funds will crush most fund managers. said private equity is drowning in shameful excess. said all of this in a room full of people who manage other people's money for a living. not one of them pushed back.

a hedge fund analyst at a top firm told me this is the first thing they send every new hire on the desk. not a book. not a model. a 42-minute video of a 96-year-old man explaining why you're going to be wrong and how to catch it before it costs you everything.

40 million people know his name. almost none of them have watched him break down the 25 ways their own brain works against them.

the lecture is free. he died the following year. it's right there in the video.

One of the 25 that stuck with me: he said most people can't sit still with a trade, they flinch at the wrong moment because emotion gets there before logic does.

That's basically why I stopped trading by hand and let a quant bot run the strategy instead — takes the flinching out of the equation entirely.

I’ve been using this for a while now and would be happy to show anyone interested how it’s all set up. Comment below or DM me "NOW" and I'll walk you through it — free access.

[Soloway @0xSoloway]

https://t.co/u7L5Tuzgxb

[Ethan @EthanXvip]

An MIT professor hands a student five dollars and says: send any amount to a stranger in the room. Whatever you send triples. How much comes back is entirely up to the stranger.

The rational move is to send nothing. Every dollar of trust you hand over, you might just lose.

But most students give away almost everything. And most strangers send back more than half. The math says hold onto your money. The room disagrees.

Then the professor runs a different version of the game. Same cash, same room. One student splits the money, the other can only accept. No rejecting, no consequences for keeping too much.

The offers shrink right away. Not to zero, but just enough to reveal the line between generosity and strategy.

One year a student got Swiss chocolate instead of cash. She was lactose intolerant. She gave away every last piece. The professor noted it, the class laughed, and nobody caught the point.

For her, generosity cost nothing. When giving is free, everyone becomes generous. But the moment real money is on the table, the room splits into the same two groups every semester: people who send first, and people who wait.

Labor, capital, arbitrage, insurance. Four ways to make money. All four demand the same opening move: you hand over value before you see anything back.

A paycheck comes after the work. Interest comes after the deposit. A payout comes after the bet. A claim gets paid after the premium.

The lecture is free. MIT filmed it years ago. The game runs every semester. The split barely shifts.

Making the first move costs nothing. Finding out whether it comes back, that's the expensive part.

That is precisely why I held off on trading for so long: I didn’t want to send money first without having any idea what I’d get in return.

Eventually, I spent some time testing a quantitative (quant) bot to eliminate the guesswork.

I’ve been using it for quite a while now, so I no longer view it as a shot in the dark. I’d be happy to show anyone interested how it’s all set up—just send me a private message with the word "NOW"

[Di Krass @Di_Krass_]

https://t.co/uqpWlmfjLV

[Ethan @EthanXvip]

This guy literally explained why some people become successful while other stay average.

The reason is uncomfortable. Game Theory

Watch this:

[DAN KOE @thedankoe]

https://t.co/7l7Jef99QZ

[Ethan @EthanXvip]

🚨 Skip Netflix tonight.

Instead, watch this 2 h 34 m Stanford lecture.

Honestly the best explanation I've seen of how ChatGPT and Claude actually work.

No fluff, no marketing spin, just the real thing.

Tokenization, BPE, the transformer, attention, how the model trains, how it generates a response one token at a time. It's all there, laid out clearly.

Doesn't matter if you've never written a line of AI code or you're building agents every single day. By the end, a bunch of stuff you've been trying to piece together for years just clicks.

Here's the core of it: text gets turned into numbers the model can actually chew on through BPE tokenization. The entire job of a language model comes down to guessing the next token, nothing more. Attention is what lets tokens "talk" to each other inside the transformer. During training, the model is pushed to raise the probability of the whole sequence at once (that's the NLL loss). And during generation, it builds the answer one token at a time.

Stuff that usually takes people a year or two to piece together, this hands it to you in one sitting.

Clear your evening.

No exaggeration, this might be the most useful thing you watch this month.

[Casper @caspr_exe]

https://t.co/wbD7cRDdND