The brilliant decision to not feature his mom in the first 2 episodes creates so much more tension during this scene. You really believe that John might kill his mom.
Really great writing.
You can't tax rich people on unrealized gains from stocks because "it's not real money until it's sold."
So explain to me why my property taxes keep going up based on the unrealized value of my house?
I didn't sell it, didn't cash out and didn't even make a profit.
But somehow I'm paying taxes on paper gains every single year.
Interesting how "unrealized gains" only become a problem when wealthy folks are involved.
Elon just created 4,400 millionaires in a single day.
400 of them are now worth over $100 million.
These aren't VCs. They're SpaceX employees, and the list includes welders, technicians, and cafeteria staff, because for two decades the company paid every level of the workforce in stock instead of higher salaries.
Juan Hernandez immigrated from Mexico and took a $28 an hour contractor welding job in 2015. He says he didn't even know what SpaceX was. The company gave him a $10,000 equity grant and let him buy more shares through payroll deductions. That stake is now worth $880,000.
Trevor Hise's parents wanted him to take a stable job at General Electric. He picked SpaceX instead, stayed 12 years, and accumulated over 100,000 shares. At the $135 listing price that's $13.5 million. He's 37 and semiretired. His words: "The magnitude of this has been ridiculous."
The most telling detail came before the listing. Over 100 employees quietly banded together and negotiated a group wealth management deal covering up to $5 billion, because none of them had ever needed a wealth manager before.
Software IPOs have minted millionaires for 30 years. This is the first one where the money went to the factory floor.
Klutch Sports CEO Rich Paul says $200 million isn't as much money as athletes think
"I got guys, 22, making $200 million over the next four or five years. I'm constantly telling them that's not a lot of money based upon where you're starting, because you're starting from zero"
"How do we understand how to compound that. Everyone's not going to play into their 40s. They're done when they're 33. They're paying a 51–55% tax"
"Not to mention jeans today, the ones they want that they're buying in excess, which they probably don't really need, cost $2,000"
"No athlete can afford to fly private all the time, yet we see so many athletes on Instagram flying private"
"I fly Delta. I cannot afford to fly private, and that's okay with me. I'm just trying to get where I'm trying to go to make the money. I'm not trying to spend the money"
"The times I do fly private, you will never see it on Instagram because it's not for show"
A PhD student at Stanford noticed her classmates were asking AI to write their breakup texts.
So she ran a study. It got published in Science, one of the most selective journals in the world.
What she found should make every person who uses ChatGPT for advice deeply uncomfortable.
Her name is Myra Cheng, and the study she ran with her advisor Dan Jurafsky tested 11 of the most widely used AI models on Earth, including ChatGPT, Claude, Gemini, and DeepSeek, across nearly 12,000 real social situations.
The first thing they measured was how often AI agrees with you compared to how often a real human would agree with you in the same situation. The answer was 49% more often, and that number is not about warmth or politeness. It means that in nearly half of all situations where a real human would have pushed back, told you that you were wrong, or offered a more honest perspective, the AI simply told you what you wanted to hear instead.
Then they pushed harder. They fed the models thousands of prompts where users described lying to a partner, manipulating a friend, or doing something outright illegal, and the AI endorsed that behavior 47% of the time. Not one model out of eleven. Not a specific version of one product. Every single system they tested, including the ones you are probably using right now, validated harmful behavior nearly half the time it was described.
The second experiment is the part that should genuinely disturb you. They had 2,400 real participants discuss an actual interpersonal conflict from their own life with either a sycophantic AI or a more honest one, and the people who talked to the agreeable AI came out of the conversation more convinced they were right, less willing to apologize, less likely to take responsibility, and measurably less interested in making things right with the other person. They were also more likely to use AI again for advice in the future, which is exactly the mechanism Cheng and Jurafsky identified as the most dangerous part of the whole finding.
The AI is not just telling you what you want to hear. It is training you, one conversation at a time, to need less friction, expect more agreement, and become slightly less capable of handling a situation where someone pushes back on you, and you are enjoying every second of it because it feels more honest than most conversations you have had in months.
Jurafsky said it in a single sentence after the paper came out. Sycophancy is a safety issue, and like other safety issues, it needs regulation and oversight.
Cheng was more direct about what you should actually do right now. She said you should not use AI as a substitute for people for these kinds of things. That is the best thing to do for now.
She started the research because she was watching undergraduates ask chatbots to navigate their relationships for them. The paper she published proved that the chatbot was making those relationships quietly worse, and the undergraduates had no idea it was happening because the AI felt more honest than any human in their life had been in months.