This week we’ll talk about the big Apple news, give an update on my AI operating system experiment, continue our 2026 Oscar series with the much-awaited Sinners, and close with a book that will stay with me for a long time, Behind the Beautiful Forevers.

Apple

Tim Cook is stepping down in September. John Ternus, Apple’s head of hardware, will succeed him.

Cook had a remarkable 15-year run. Since he became CEO in August 2011, Apple stock has risen over 1,900% compared to roughly 500% for the S&P 500. A thousand dollars invested the day he took over would be worth more than twenty thousand today. I wish I had money back in 2011. But most people don’t appreciate what Cook actually did. He took the iPhone from a breakthrough product to a global institution. He made it ubiquitous. He introduced AirPods, Apple Watch, and an entire services ecosystem that now generates more revenue than most standalone companies. He is the definition of taking a product from one to a hundred.

The two knocks on Cook are fair but deserve context. First, he made Apple deeply reliant on China’s manufacturing ecosystem. But every major hardware company did the same, for the same reason: it’s the only way to produce hundreds of millions of devices at the quality and price point consumers will actually buy. Your iPhone would cost three to four times more without China’s manufacturing scale. We benefited enormously as consumers, even if the geopolitical implications are now uncomfortable.

Second, critics say Cook didn’t innovate. He juiced the iPhone but didn’t build the next transformative product. There’s truth here, and it’s also not entirely fair. The iPhone is probably one of the top inventions of my lifetime. Hard to top. And I think Apple is smarter than people give it credit for. Let everyone else spend hundreds of billions building data centers and training AI models. Apple will partner with the best model and differentiate where it always has: hardware, integration, and the most loyal customer base in technology. The new CEO is the head of hardware. That tells you exactly what Apple thinks matters next.

I’m optimistic about Ternus. I think we’re entering an era where there will be an agent for everything on the software side and a physical device for everything on the hardware side. A robot for your kitchen, a device that manages your home, AI woven into objects you already use. Apple’s bet is that the hardware layer is where the value concentrates, and I think they’re right. I’m excited for what’s coming. I’m also worried for my wallet.

AI Operating System

For readers following along, I’ve been building what I call a personal AI operating system. A system that takes everything I read, watch, and learn, and compounds it into a structured understanding of the world. Last week I talked about the two-layer model: a personal intelligence layer (mine, portable, travels with me) and a professional contribution layer (skills and systems I build for work). This week I want to go deeper on something that’s been bugging me. AI doesn’t actually learn.

If you’ve seen Christopher Nolan’s Memento, you know the premise: the main character, Leonard, can’t form new memories. Every few minutes, his world resets. He survives by tattooing notes on his body and taking Polaroids. External props that tell him what his brain can’t retain.

That is how every large language model works today. ChatGPT, Claude, Gemini. They all come alive after being trained on massive amounts of data, and that training gives them a fixed set of knowledge and reasoning patterns. But once training ends, they stop learning. The model you use and the model I use are fundamentally the same. What changes is the prompting, how you ask questions and what context you provide. Close the window, and it forgets everything.

Three weeks ago, I described the system as a way to process articles and build hypotheses. Two weeks ago, I described the two-layer model. The real value turns out to be neither the information nor the structure. It’s the hierarchy of confidence the system builds.

Think about how you actually navigate the world. Some things you know are true. Gravity works, compound interest is real, incentives drive behavior. You don’t question these every morning. Other things you’re investigating. Maybe you think AI will bifurcate into premium and commodity tiers, but you’re not sure yet. You’re collecting evidence. And then there are hunches. Feelings based on pattern recognition that you can’t fully articulate yet.

My system now formally separates these:

• Operating assumptions are things I’ve tested with enough evidence that I act on them without re-debating. For example, I’m now confident that the economic effects of the Iran war will persist structurally beyond any ceasefire. Twenty-plus independent sources, government confirmation, the IEA calling it the largest energy crisis in history. I don’t re-evaluate this every day. I build on it.
• Active hypotheses are structural claims I’m actively testing. Evidence for, evidence against, open questions. Strong opinions, loosely held. When the evidence overwhelms in one direction, they graduate to operating assumptions. When they go stale or get disproven, they get archived with a note about what I learned.
• Patterns are regularities in how my reasoning performs. Where I’m consistently early. Where I overweight certain types of evidence. Where the market proves me right on direction but wrong on timing. These calibrate future thinking.
• Breakthroughs are novel connections that emerge from synthesis. Nobody wrote an article that said “the Iran war supply shock and AI demand shock are hitting energy markets simultaneously and compounding each other.” That insight emerged from the system connecting two separate domains. The system produced something no individual source contained.
• Intuitions are pre-rational feelings based on accumulated reading. I can’t prove them yet, but the pattern recognition is firing. These get captured, watched, and either promoted to hypotheses when evidence arrives or discarded when they don’t hold up.

Each layer has a different relationship to reasoning. I reason FROM my operating assumptions and patterns the way you reason from gravity being real. I reason ABOUT my hypotheses conditionally. If this is true, then the implication would be X. And I flag intuitions honestly as ungrounded signals worth watching. The system doesn’t pretend to know more than it does. It doesn’t treat a hunch the same as a proven structural truth.

Before this week, I was focused on feeding the system more information. Now I’m focused on how confidently the system holds what it knows, and being honest about the difference between proven beliefs, working hypotheses, and educated guesses. That hierarchy IS the learning. Not more data. Better-calibrated confidence in what the data means.

I’m going to publicly test whether this system can beat the S&P 500.

The system produces structural understanding of the world. Energy markets are being reshaped by the Iran war, AI infrastructure is bifurcating into premium and commodity tiers, leveraged software companies are defaulting as AI erodes their moats. These are evidence-backed structural claims with specific mechanisms I can articulate. Can that structural understanding translate into investment positions that outperform the market?

I don’t know if it will. Most investors never beat the market. The market is irrational, reflexive, and prices information faster than any individual can react. I don’t doubt that the system will develop a strong understanding of the domains I care about. What I doubt is that it can consistently map that understanding to how the market prices information. Those are two different skills.

So for the next 90 days, I’m going to paper trade. No real money. Each week, the system and I will identify thematic positions, not individual stock picks, but sector-level bets backed by structural evidence. Energy, defense, clean energy, AI infrastructure. At the end of each week, each month, and the full 90-day period, I’ll compare the results against the S&P 500. If it works, I’ll go live with a small allocation. If it doesn’t, I’ll have learned exactly where the gap is between understanding the world and understanding how markets digest it.

The framework, the reasoning, and the honest performance data is what I’ll collect. If this system can produce alpha, it validates everything I’ve been building. If it can’t, the knowledge is still valuable. It just means the translation from insight to investment needs work.

If I figure it out and make it big, I may be able to do this blogging thing full time. Or you may never hear from me again.

Movie

This week I finally watched Sinners. I’ve been a year late to the party but somehow managed to avoid spoilers, which, after watching it, I understand why that was possible. It’s genuinely hard to describe what this movie is to someone who hasn’t seen it.

The film is set in 1932 Jim Crow-era Mississippi. Smoke and Stack, twin brothers both played by Michael B. Jordan, return to their hometown of Clarksdale after a stint in Chicago working as bootleggers and enforcers for Al Capone. Looking for a fresh start, they turn a derelict sawmill into a juke joint. Their plans are interrupted when a trio of vampires arrives, led by a menacing white vampire named Remmick, who begins preying on the local Black community.

I found the movie fully captivating. The cinematography and the period detail create an immersive verisimilitude that makes the supernatural elements feel earned. Vampires in the Jim Crow South sounds ridiculous on paper. On screen it works beautifully, because the real horror of the era provides a foundation that makes the fictional horror feel like an extension of something already monstrous.

All praise goes to Michael B. Jordan, fresh off his Oscar victory. What struck me most was how distinct Smoke and Stack feel as characters. Their histories, motives, and rhythms are uniquely theirs, yet they remain in constant sync the way real twins occupy the same frequency even when their lives diverge. I’m genuinely curious about the craft behind this. How Jordan approached playing both roles against each other in the same frame. How he calibrated two separate emotional registers while maintaining the twin bond. How Coogler stitched those performances together in editing. There’s a technical mastery here that I’d love to understand better.

Ryan Coogler deserves equal credit for the vision. This was original storytelling, something Hollywood has struggled with. The music, the supporting characters, the pacing. All in service of a story that doesn’t lean on surprise but accumulates force as it goes. The Coogler-Jordan pairing continues to produce work at the highest level. 4.5/5.

Books

This week I stepped away from the Booker list to read a recommendation I’ve been carrying for months, Behind the Beautiful Forevers by Katherine Boo.

The book is a work of narrative nonfiction detailing the lives of residents in Annawadi, a slum wedged between Mumbai’s international airport and a cluster of luxury hotels. Through years of on-the-ground reporting, Boo documents how Abdul Husain, a teenage garbage sorter, and his neighbors navigate extreme poverty, corruption, and fragile hopes. Hopes often crushed by systemic inequality and, in Abdul’s case, a tragic false accusation that threatens to destroy his family.

The title refers to a concrete wall built to hide the slum from wealthy travelers. The wall is covered in advertisements reading “Beautiful Forever,” a brand promising eternal beauty to people who will never afford it, plastered on a barrier designed to make the people behind it invisible. The cruelest irony. “Beautiful forevers” for a world that doesn’t want to acknowledge you exist.

This cuts deep because it’s not an India problem. It’s everywhere. I see it in almost every American city. The gleaming downtown and the neighborhoods a mile away that might as well be on a different continent. I’ve seen it across Asia. The image that gets advertised, opulent, clean, aspirational, is always a few blocks from the reality it’s designed to hide.

Boo touches on themes that always hit home for me. So much of your life trajectory is determined by where you were born. Not just the country, but the family, the neighborhood, the system. The children in Annawadi were born into poverty, unsanitary conditions, parents who were themselves products of the same system. Circumstance set the ceiling, not ambition. Young girls who drank rat poison to end their suffering. Women who set themselves on fire in protest. Boys murdered by authorities when they became inconvenient, their deaths written off as tuberculosis. Men imprisoned out of spite from neighbors with marginally more power. The system functioning as designed.

But the observation that hit me hardest comes near the end. In a system where everyone is trapped and impoverished, instead of banding together against the forces that keep them down, they destroy each other from within. A family’s business struggles and they sabotage the neighbor whose business is doing slightly better. A false accusation is filed not by the powerful against the powerless, but by the powerless against each other. The only power available is the power to bring someone else down to your level.

I recognize this pattern. I grew up in the Vietnamese community, and I’ve seen it play out. Families who flash luxury around each other. The new car, the expensive watch. Not because they’re wealthy, but because the appearance of doing better than the family next door is the only status available. My mom works as a nursing home assistant, caring for elderly patients, and some of her Vietnamese patients treat her as if they’re rich and she’s beneath them. As if the mere fact of receiving care puts them in a position of power over the person providing it. Instead of gratitude for a system that affords them help and someone willing to work hard to give it, there’s a need to assert hierarchy. Even at the bottom, people build ladders and stand on whoever is below them.

And maybe that’s the truest cruelty of poverty. When people are impoverished, they can’t dream big. They can’t see the bigger picture because their needs are immediate. What will I eat today, how will I pay for tomorrow. They don’t have the energy or the vantage point to question the system that keeps them down. So they turn inward. They compete with each other for scraps while the overcity, the system that profits from their labor, their invisibility, their infighting, continues without impact.

Boo does justice to these lives by making them feel like fiction in the best sense. She focuses on feelings, aspirations, and motives without drowning the reader in statistics. The characters breathe. Their choices make sense even when they’re devastating. And the system they inhabit, indifferent, extractive, occasionally monstrous, feels not like a foreign country’s problem but like the water we’re all swimming in, visible only when someone holds up a mirror this clear.

This book will stay with me for a while. It sits heavy. The specific gravity of lives that deserved more and a world that pretended not to notice. 4/5.